Indian Business Groups and Other Corporations: Comparative Organisational Perspectives on Indian Corporate Firms (India Studies in Business and Economics) 9819950406, 9789819950409

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India Studies in Business and Economics

Achin Chakraborty Indrani Chakraborty   Editors

Indian Business Groups and Other Corporations Comparative Organisational Perspectives on Indian Corporate Firms

India Studies in Business and Economics

The Indian economy is one of the fastest growing economies of the world with India being an important G-20 member. Ever since the Indian economy made its presence felt on the global platform, the research community is now even more interested in studying and analyzing what India has to offer. This series aims to bring forth the latest studies and research about India from the areas of economics, business, and management science, with strong social science linkages. The titles featured in this series present rigorous empirical research, often accompanied by policy recommendations, evoke and evaluate various aspects of the economy and the business and management landscape in India, with a special focus on India’s relationship with the world in terms of business and trade. The series also tracks research on India’s position on social issues, on health, on politics, on agriculture, on rights, and many such topics which directly or indirectly affect sustainable growth of the country. Review Process The proposal for each volume undergoes at least two double blind peer review where a detailed concept note along with extended chapter abstracts and a sample chapter is peer reviewed by experienced academics. The reviews can be more detailed if recommended by reviewers. Ethical Compliance The series follows the Ethics Statement found in the Springer standard guidelines here. https://www.springer.com/us/authors-editors/journal-author/journal-aut hor-helpdesk/before-you-start/before-you-start/1330#c14214

Achin Chakraborty · Indrani Chakraborty Editors

Indian Business Groups and Other Corporations Comparative Organisational Perspectives on Indian Corporate Firms

Editors Achin Chakraborty Institute of Development Studies Kolkata Kolkata, West Bengal, India

Indrani Chakraborty Institute of Development Studies Kolkata Kolkata, West Bengal, India

ISSN 2198-0012 ISSN 2198-0020 (electronic) India Studies in Business and Economics ISBN 978-981-99-5040-9 ISBN 978-981-99-5041-6 (eBook) https://doi.org/10.1007/978-981-99-5041-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Paper in this product is recyclable.

Preface and Acknowledgments

With changes in policy regimes and institutional environments over time and across countries, which have culminated in more developed and complex financial markets and better-designed regulations, it is unlikely that any generalizable explanation of persistence of business groups in the present world can be arrived at. Empirical evidence shows that the dominance of the business groups in the Indian economy has not declined in the post-reform period. The diversity of experiences of business groups in different countries calls for more country-specific research on them as they form the dominant mode of economic organization in many countries. The literature on business groups in India—ranging from the analytically rigorous studies informed by organizational–institutional perspectives, based on such data sources as Prowess, on the one hand, to media commentaries and investigative reports by journalists based on controversial facts, on the other—shows the contested nature of the issues. A comprehensive understanding of the role of business groups vis-à-vis that of other corporate firms in the Indian economy was therefore needed. With the aim of throwing more light on these issues, the Institute of Development Studies Kolkata (IDSK) organized a national conference on “Rethinking the Role of Business Groups in Contemporary India: Analyses, Reviews and Reflections”, which was held during 28–29 March, 2018 at the institute’s campus. The present volume is the culmination of the papers presented at the conference. Many people have helped us in this endeavor. We are greatly indebted to Amiya Kumar Bagchi, former Director and presently Emeritus Professor of IDSK, for constant support and inspiration in organizing the conference. We are also indebted to the faculty members and administrative staff of IDSK for helping us to organize the conference successfully. We finally express our gratitude to all the scholars who have made contributions to this volume, for their active participation in the conference which enriched the quality of deliberations, as well as their sincere cooperation

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Preface and Acknowledgments

which made it possible for us to prepare the volume. Finally, we thank Springer Nature, for agreeing to publish this volume. Kolkata, India

Achin Chakraborty Indrani Chakraborty

Contents

1

Business Group Firms in India: A Short Introduction . . . . . . . . . . . . Indrani Chakraborty and Achin Chakraborty

2

The Regime of Capital Accumulation, the Hindu Undivided Family and the Business Group in Independent India . . . . . . . . . . . . . Chirashree Das Gupta

13

Corporate Response to Public Policy Changes: Some Intriguing Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Dennis Rajakumar

29

Ownership Control and Board Governance of Indian Business Groups: Continuity or Change? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jayati Sarkar

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4

1

5

The Multi-entity Structure and Control in Business Groups . . . . . . . 111 Surajit Mazumdar

6

Business Group Affiliation, Financial Distress and Corporate Investment-Cash Flow Sensitivity: Evidence from India . . . . . . . . . . . 129 Jitendra Mahakud and Gaurav Gupta

7

Promoter Ownership and Performance in Publicly Listed Firms in India: Does Group Affiliation Matter? . . . . . . . . . . . . . . . . . . 175 Ansgar Richter and Indrani Chakraborty

8

Differences in the Performance of Group-Affiliated and Stand-Alone Firms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Jhuma Mukhopadhyay

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Contents

Related Party Transactions and Stock Price Crash Risk: Evidence from India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Ekta Selarka and Subhra Choudhury

10 Minsky’s Financial Instability Hypothesis: A Theoretical Engagement in the Indian Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Rohit Azad

Editors and Contributors

About the Editors Achin Chakraborty is a Professor of Economics at the Institute of Development Studies Kolkata (IDSK). He was earlier at the Centre for Development Studies, Thiruvananthapuram. He received Ph.D. in Economics from the University of California at Riverside, USA. He has published widely in such journals as Economic Theory, BMJ Global Health, Social Indicators Research, Economics Bulletin, Journal of Quantitative Economics. He jointly authored the book ‘Limits of Bargaining: Capital, Labour, and the State in Contemporary India’ (2019) and co-edited three books—‘The Land Question in India: State, Dispossession and Capitalist Transition’ (2017), ‘Changing Contexts and Shifting Roles of the Indian State’ (2019) and ‘Capital’ in the East (2019), with the latter being translated in German as well. Indrani Chakraborty is a Professor of Economics and currently the Director of the Institute of Development Studies Kolkata. She was formerly at the Centre for Development Studies, Thiruvananthapuram. She received Ph.D. in Economics from the University of Calcutta and is a recipient of CICOPS scholarship and Liverpool-India Fellowship to work at University of Pavia and University of Liverpool Management School, respectively. She has published widely in reputed journals and contributed to many book volumes on the impact of capital inflows, the role of financial development on economic growth, capital structure of corporate firms, impact of reforms on firms’ performance, impact of mergers and acquisitions on firm performance and so on. She authored ‘Exploring What Drives Indian Stock Market During Covid19: Fads or Fundamentals’ (2023) and co-edited ‘Market, Regulations and Finance: Global Meltdown and the Indian Economy’ (2014).

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Editors and Contributors

Contributors Rohit Azad Jawaharlal Nehru University, New Delhi, India Achin Chakraborty Institute of Development Studies Kolkata, Kolkata, India Indrani Chakraborty Institute of Development Studies Kolkata, Kolkata, India Subhra Choudhury Madras School of Economics, Chennai, India Chirashree Das Gupta Centre for the Study of Law and Governance, Jawaharlal Nehru University, New Delhi, India Gaurav Gupta FORE School of Management, New Delhi, India Jitendra Mahakud Department of Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, India Surajit Mazumdar Centre for Economic Studies and Planning, Jawaharlal Nehru University, New Delhi, India Jhuma Mukhopadhyay Independent Researcher, Kolkata, India J. Dennis Rajakumar EPW Research Foundation, Mumbai, India Ansgar Richter Rotterdam School Rotterdam, Netherlands

of Management,

Erasmus University,

Jayati Sarkar Indira Gandhi Institute of Development Research, Mumbai, India Ekta Selarka Madras School of Economics, Chennai, India

Chapter 1

Business Group Firms in India: A Short Introduction Indrani Chakraborty and Achin Chakraborty

1.1 The Backdrop Scholarly interest in business groups has intensified in recent years, perhaps because of the long history of persistence and resilience of business groups in spite of highly diverse and occasionally changing institutional contexts in which they thrive in different countries. A business group could be seen as “an informal coalition of legally independent firms, operating in single or multiple industries, which are bound together by persistent formal (equity) and informal (family) ties” (Khanna and Yafeh 2007).1 Historically, business activities in India saw the emergence of the business houses in the latter half of the nineteenth century. Tatas, Khataus, Birlas and Mafatlals began their journeys around that time. The business houses gradually rose to dominance in the twentieth century. It is rather commonplace to seek explanation of the origin of the business groups in the prevailing institutional contexts, which were typically characterized by under-developed capital markets and high transaction costs. However, with changes in policy regimes and institutional environments over time and across countries, which have culminated in more developed and complex financial markets and better-designed regulations, it is unlikely that any generalizable explanation of persistence of business groups in the present world can be arrived at. The diversity of 1 Drawing on a host of definitions of business groups, Sarkar (2010) provides a consolidated one as follows: “an agglomeration of privately held and publicly traded firms operating in different lines of business, each of which is incorporated as a separate legal entity, but which are collectively under the entrepreneurial, financial, and strategic control of a common authority, typically a family, and are interlinked by trust-based relationships forged around a similar persona, ethnicity, or community” (p299).

I. Chakraborty (B) · A. Chakraborty Institute of Development Studies Kolkata, Kolkata, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_1

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experiences of business groups in different countries calls for more country-specific research on them as they form the dominant mode of economic organization in a number of countries, especially in the developing world. The literature on business groups in India—ranging from the analytically rigorous studies informed by organizational–institutional perspectives, based on such data sources as Prowess, on the one hand, to media commentaries and investigative reports by journalists based on controversial facts, on the other—shows the contested nature of the issues. A comprehensive understanding of the role of business groups in the Indian economy would perhaps require critical inquiries using all possible sources of information. This book intends to fill this gap. Indian business groups, often referred to as “Business Houses”, date back to the colonial times. About three-fourths of the largest companies in India are family businesses. There are about 400 business groups in India with variation in size and levels of diversification. The role of the business groups in the evolution of the Indian economy is believed to have changed since the economic reforms initiated in 1991, which has been supported by a number of empirical studies. For example, the pattern of distribution of firms in general, and group-affiliated firms in particular, and capital structure of those firms have been found to have changed considerably (Chakraborty 2013). If we group the firms into four categories, namely, stand-alone firms with low/high leverage and group-affiliated firms with low/high leverage, we find that in India the percentage of stand-alone firms having low leverage has increased sharply since 1990. In the pre-reform years, the percentage of firms belonging to the lowleverage and group-affiliated category was the highest among the four categories, and reversing the trend, the share of this category reached the lowest position in 2010. From the distribution of firms among the four categories, it is evident that stand-alone firms became the dominant category in terms of their number during the first two decades of reforms. However, the presence of business groups in the Indian context is still significant in terms of their overall influence on the business ecosystem (Chakraborty 2013). Since the mid-1980s, the Indian economy experienced acceleration in the growth rate of GDP, growing roughly at 6% per annum, which is remarkable compared to its performance in the earlier decades since independence. This growth episode triggered a debate on whether the orientation of the Indian economic policies had been “pro-business” or “pro-market” (Kohli 2006, 2007; Rodrik and Subramanian 2004; Panagariya 2008; Mody et al. 2011). While Kohli (2006, 2007) argued that it was a pro-business orientation of the Indian state—in which business groups formed the main political ally—that contributed to the acceleration in growth, Panagariya (2008) differed and preferred to characterize the policy direction in the 1980s as pro-market rather than pro-business. Both, however, agreed that from 1950 to 1980 India followed a statist, import substitution model of development. Kohli argued that partially influenced by the East Asian model of development the Indian state followed a growth-oriented path with a visible hand of the state in which the business class was encouraged to play the leading role. In support of his argument, he presents a detailed account of how India’s two older national chambers of commerce, namely, Federation of Indian Chambers of Commerce and Industry (FICCI) and Associated Chambers

1 Business Group Firms in India: A Short Introduction

3

of Commerce and Industry (Assocham) gradually gave way to the Confederation of Indian Industry (CII), which emerged as the representative of the more modern segment of industries that saw a better future in embracing the global markets. CII developed close ties with bureaucracy, and the government invited the private sector to take part in the decision-making process. External sector liberalization as one of the most important strategies of economic reforms since 1991 was much favored by the members of CII. Even the older business houses that thrived well during the import substitution regime of the earlier period eventually joined the advocates of external trade liberalization. This process of transition of the India’s chambers of commerce is indicative of how Indian capital joined hands to promote its interest in the liberalizing regime and became a part of the growth process in the post-reform period. By contrast, the pro-market view regards the reduced restrictions and external liberalization as the main drivers of changes in performance (Panagariya 2008). The liberalization measures that had been undertaken since 1991 include removal of import quotas, reduction of tariffs, devaluation of currency, liberalization of foreign investment and easing of restrictions on external financial transactions. These changes are supposed to have pushed the Indian firms towards greater efficiency by exposing them to competitive pressures. There was indeed a significant increase in the number of stand-alone firms in the mid-1990s. There was a simultaneous increase, but at a smaller level, in the number of new business houses as well (Mody et al. 2011). Mody et al. (2011) observed persistence of profits in the Indian corporate sector in the post-reform period till the early 2000s, which could be attributed to improved performance. They argue that the persistence of profits indicates that Indian corporate firms were able to withstand competitive pressures from firms in the same industry. Their study shows a consistent relationship between increase in firmlevel profitability and market share for both business groups and stand-alone firms, and they argue that it was due to the effect of better underlying firm performance rather than the exertion of market power.

1.2 Business Group Affiliates and Stand-Alone Firms Against this larger backdrop if we further narrow down the focus on the two groups of corporate firms—business group affiliates and stand-alone firms—a comparative perspective almost naturally comes to one’s mind. The nature of corporate control differs between group-affiliated firms and stand-alone firms, which has different implications for firm performance. There is a large literature on the performance differences between group-affiliated and stand-alone firms. It is generally believed that business groups have the advantage of internal capital, labor and product markets which help them resolve the so-called “institutional void” (Khanna and Palepu 2000). Institutional void in the developing countries arises when specialized intermediaries that typically provide these services in developed countries are absent. The Indian

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economy in the pre-reform era could be seen as characterized by greater imperfections in the markets for capital, product and managerial labor, and business groups were supposed to have the necessary resources and capabilities to overcome the problems through their internal markets. However, with changes in policy regimes and institutional environments in India due to economic reforms, which have culminated in more developed and complex financial markets and better-designed regulations, it is observed that there is no performance difference between group-affiliated firms and stand-alone firms in post-reform India (Richter and Chakraborty 2015; Mitra and Pattanayak 2013; Jadhav and Reddy 2017; Zattoni et al. 2009). In a similar vein, Sarkar (2010) shows that during the period from 1991 to 2006, the share of groupaffiliated firms in total assets declined from 85% in 1991 to 75% in 2006. However, she observes that the share of top-most groups increased during this period. Similar observation emerges from a more disaggregated study by Jadav and Reddy (2017), which divided the business group firms between top 30 business groups and other group firms for the period from 1990 to 2012. They show that the dominance of the top 30 business groups has actually increased while that of the rest of the groups has declined. Therefore, in a sense, the dominance of the business groups in the Indian economy has not declined in the post-reform period as the concentration in the top 30 business group firms has increased significantly. We extend the analysis of Jadav and Reddy (2017) here for comparing different classes of firms, including top 50 business groups, other business group firms, and stand-alone firms, for the years 2010, 2015 and 2020 to have a comparative picture and report the results in Tables 1.1 and 1.2. Both the tables show continuing dominance of business group firms during the 10-year period. However, between the top 50 and the rest of the business group firms, the importance of the latter has significantly increased in terms of total assets as well as total sales. This is in conformity with the finding of Jadav and Reddy (2017) that the controlling power of the Indian corporate business is largely concentrated in the hands of business groups till now. However, both in terms of assets and sales, the top 50 business groups’ shares have declined. The share of the stand-alone firms in total sales has increased significantly in this period. A particular difference that has frequently surfaced in the literature is that the group affiliated firms are believed to be less transparent than the stand-alone firms, and therefore external monitoring of the former poses more challenges than it does in the latter type of firms. Given their more complicated structures, business groups Table 1.1 Distribution of assets across firms Year

Total assets (Rs. Million) Top 50 BG

Other BG

Stand-alone

Top 50 BG

Other BG

Stand-alone

2010

11,788,754

41,097,983

6,668,421

19.79

69.01

11.19

2015

7,159,397

85,003,645

14,242,910

6.72

79.88

13.38

2020

22,903,121

1.4E + 08

24,134,833

12.25

74.83

12.90

% of total assets

(Source Authors’ calculation from prowess data)

1 Business Group Firms in India: A Short Introduction

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Table 1.2 Distribution of sales across firms Year

Total sales (Rs. Million) Top 50 BG

Other BG

% of total sales Stand-alone

Top 50 BG

Other BG

Stand-alone

2010

12,938,933

9,093,368

3,131,620

51.41

36.13

12.44

2015

33,474,148

15,806,825

6,230,707

60.30

28.47

11.22

2020

15,808,194

17,271,500

8,281,320

38.22

41.75

20.02

(Source Authors’ calculation based on prowess)

are also known to have more opportunities to engage in questionable practices to the detriment of minority shareholders. They are also better equipped to insulate themselves from strong regulation and monitoring because of their generally better links to the power that be. It has been argued that business groups expropriate minority shareholders through entrenchment (Khanna and Yafeh 2007; Morck et al. 2005), over-exploit natural resources by exercising their power to manipulate, and engage in lobbying with the power-that-be to grab more than their fair share (Faccio 2006; Kim 2008; Hillman et al 2004; Lawton et al 2012). Business groups also engage in what is called “tunneling of resources through pyramids” at the expense of minority shareholders (Bertrand et al. 2002; Johnson et al. 2000). In a business group, typically a single family completely controls several independently traded firms but has significant cash flow rights in only a few of them. This discrepancy in cash flow rights between the different firms that the family controls creates strong incentives to expropriate. The controlling group members tend to transfer profits across firms—from where they have less cash flow rights to those where they have high cash flow rights. The transfer can be made through high-interest loans or selling assets to each other at prices different from market prices. Thus with small investment, controlling owners exercise control over the large number of companies through pyramiding, and the practice of tunneling may have serious consequences on the growth in the equity market and overall financial development (Bertrand et al. 2002). Almeida and Wolfenzon (2006) argue that pyramids are formed because they magnify a given level of personal wealth into control over corporations. As a well-functioning capital market requires that the minority shareholders benefit from their holdings, tunneling may pose a serious obstacle to financial development. It is also argued that because of their larger size relative to the rest of the economy, large pyramidal groups enjoy a price setting power in their domestic capital market (Morck et al. 2000). Thus, the frictions in the underdeveloped capital markets may persist in an emerging economy, due to the presence of pyramidal groups. Moreover, owner managers in group firms may pursue objectives other than profit maximizing to increase their private benefits instead of maximizing firm value. It has also been argued that strong dominance by the family business group firms has led to oligarchic control in corporate affairs in India, which is considered to be a major barrier to growth of entrepreneurship and innovation in India. An economy with extensive pyramidal structure tends to experience less innovation than what

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should otherwise be (Morck et al. 2005). Because start-ups face difficulties in raising finance, they would invest less in innovation. On the other hand, pyramidal firms with large shareholders will be more interested in tunneling resources from firms with low cash flow rights, and there will be less incentive for them to innovate. Using crosscountry data, Fogel (2006) finds evidence in support of this. She also observes that countries with oligarchic family control in the corporate sector are likely to have worse socio-economic outcomes. She found that oligarchic family control is more prevalent in those countries where bureaucracies are less efficient and political rentseeking is prevalent and financial markets are less developed. This implies that larger corporate groups with concentrated ownership and control emerge as a response to poor institution, but are likely to develop a symbiotic relationship with the very institutions, which comes in the way of maturation of the institutions. Thus, highly concentrated business groups perpetuate poor institutions and poor institutions in turn benefit the business groups. There is a mutually reinforcing relationship between the two and hence oligarchic family control is harmful for economic growth and social welfare, Fogel argues. It seems that the core competence of many business groups in India is their ability to influence politicians to tilt policies in their favor. These firms, and the groups they belong to, influence governments in many ways—through campaign contributions, direct lobbying, extending the membership of politicians on company boards, and quite often through bribery. Oligarchic capitalism leads to economic entrenchment which is defined as the “concurrence of oligarchic capitalism, weak institutions and slow growth in a stable but Pareto-inferior equilibrium” by Morck et al. (2005). Government policies are endogenous in the sense that oligarchic groups use their resources for political lobbying; and lobbying costs are usually lower for the controlling owners of pyramidal groups than for the managers of stand-alone firms. Moreover, the transaction costs are also lower for pyramidal group firms. However, due to political connections, these business group firms enjoy preferential access to government subsidies, financing from government-owned enterprises and banks, tax breaks and are often exempted from rigid regulations (Shleifer and Vishny 1993, 1994). Corporate governance in business group firms thus becomes very important in the Indian context. Tunneling, as we indicated earlier, is a major concern in business groups with pyramidal ownership structure and inter-firm cash flows. Bertrand et al (2002) find that firms lower down in the pyramidal structure are less affected by industry-specific shocks than those nearer the top, which suggests that positive shocks at the bottom of the pyramid are siphoned off to the latter helping the controlling shareholders but hurting the minority shareholders. However, Khanna and Yafeh (2007) question how this logic would make them less sensitive to negative shocks. There is also some evidence (e.g., Khanna and Palepu 2000) that business group firms show superior performance than stand-alone firms. Kali and Sarkar (2007) have argued that diversified business groups deepen the problem of the lack of transparency about within-group funds flow leading to widening of the gap between control and cash flow rights and the likelihood of tunneling also increases. This incentive for

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tunneling explains to some extent the Indian business groups’ occasional heavy investment in businesses with low profitability. Faccio (2006) further shows that political connections of businesses are prevalent in countries with higher levels of corruption and are less common in countries that have more rigorous regulations on political connections. In this connection, we argue that the unholy nexus between politicians and business groups is what largely explains the persistence and resilience of business groups in contemporary India. Several scholars have argued that weak corporate governance in business groups was the main reason for the East Asian financial crisis (Johnson et al. 2000; Mitton 2002; Baek et al. 2004, Corsetti et al. 1999). A kind of “crony capitalism” helped the business groups to borrow without difficulties and the moral hazard problem associated with this led to the crisis (Chang 2000). Thus, the dominance of the business groups in the corporate sector in India also raises the risk of a similar kind. However, some scholars disagree with this alarmist prognosis. They ask whether it can be generalized that the microeconomic governance problems of family-controlled businesses turn into macroeconomic problems (Khanna and Yafeh 2007). Besides, as Stulz (1999) argued, one may not find strong arguments to reject the Asian way of doing business. One can even view the Asian business model as a case of cooperation between business and government, which is believed to deliver more positive results in terms of growth and overall welfare (Singh and Zammit 2006).

1.3 Chapters in This Volume The 10 chapters in this book address a select number of issues with reference to corporate India, with a special focus on business groups, public policy and corporate governance. The analytical perspectives that have been adopted by the contributors are varied, which, in our opinion, have been a strength rather than weakness of the volume. The extant literature on business groups in India encompasses a wide range of subdisciplines, such as management science, institutional economics, economic sociology and so on. However, the familial basis of ownership and control of business groups remains an obscure area of study. The organization of the “business house” found legal sanction through multiple legislations spanning corporate and tax laws and forms the object of studies in “corporate governance”. On the other hand, the institution of the “family” has fallen in the ambit of the study of “personal laws”. While the first aspect is significant in establishing the institutional basis of concentration of capital combining the modalities of ownership and control, the second has implications for not only accumulation, investment and concentration of capital but also tax avoidance and evasion (Das Gupta 2013). The relationship between these two aspects and the regimes of accumulation in independent India has been largely unexplored in the otherwise growing corpus of literature on the relationships among business group, corporate governance and public policy. In Chap. 2, Chirasree Dasgupta addresses the issue of capital accumulation in the Hindu Undivided Family

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(HUF) and the business groups in India since independence. She argues that, it is the dual existence of the HUF as both a family and a firm that makes it distinct from all other institutional categories. She discusses the channels through which family control over the organizational structure of business groups and the ownership of wealth by the family generated through these structures are maintained. The interlocking of the caste Hindu patriarchal family with corporate governance institutions is formally embedded in law in India. It is the materiality of capital that forges the social entity of the family-owned business group. This materiality is formally legally embedded in the seamless interlock of the firm and the family where the firm becomes the family in the case of the HUF. This spans state codification of Hindu family law, corporate governance laws and taxation laws. She further argues that, it is capital in its material social role in the circuit of financial and capital flows, which drives the network of institutions that constitutes the “family-owned business group” in India legally. This is formally undergirded by caste, patriarchy and religion. Moreover, she shows that, this unique legal family/firm interlock is not available to Muslims, Christians, Parsis or Jews and hence constitutes a perverse legal privilege to the Hindu family. Dennis Rajakumarin Chap. 3 analyzes corporate responses to public policy changes. Using data from National Accounts Statistics and Reserve Bank of India’s Studies of Company Finances, he shows that the response of private corporate sector to the public policy changes has been in line with the expected outcomes of increasing the sector’s contribution to the growth process. Not only that the sector’s share of capital formation and savings in country’s NDP increased but also the sector aided their growth as well. However, the way corporate sector responded brought about a shift in the composition of corporate income with profit share rising considerably. This was largely attributable to the sector’s increased reliance on shareholders’ fund. With reductions in direct corporate tax rate, the incidence of corporation tax showed an upward trend. Although the sector’s engagement with the rest of the world was facilitated by trade and foreign investment-related policies, the sector continued to have lower earnings than their expenditure in foreign currencies. The chapter also reports that market valuation remained higher relative to the replacement cost (that is, Tobin’s Q exceeding unity), implying that corporate investment decisions were driven by market sentiments. This changing character of the private corporate sector has implications for income distribution as well as for achieving stability in growth, as Rajakumar argues. Jayati Sarkar in Chap. 4 analyzes how the ownership, control and board governance of Indian business groups have evolved over time against the backdrop of evolving laws and regulations in India. Her analysis is based on a panel data of group affiliated and unaffiliated firms for the period 2005–2018 during which the governance reforms that were initiated in the earlier years took root, and several new ones were introduced through revisions of existing regulation and laws. The chapter seeks to answer mainly two questions. First, have the nature of the agency problems pertinent to business groups as manifested in their ownership and control structures fundamentally changed in response to dynamic changes in their institutional environment? Second, have reforms introduced to change the ways in which

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groups are governed by the board of directors made any impact on the way these groups are actually governed? Contrary to the expectations drawn from the institutionalist perspective that the relevance of business groups that fill institutional voids will wane as markets develop, the analysis in this chapter points to the continued predominance and persistence of Indian business groups within the corporate sector. She shows that, several of the groups, such as the Tatas and Birlas, which were established in the pre-independence era, have continued to remain in leadership position with a handful of large business groups continuing to dominate the sector, irrespective of the changes in the institutional environment. Big groups have become even bigger in terms of their asset base, and changes in the relative positions of groups at the top end of the distribution have been sticky at best even after more than 100 years of their existence and continued entry of new groups from time to time. Within groups, ownership structures have become more concentrated over time, with promoters of almost of all groups now having majority control in all the listed firms of the groups. She further argues that the pervasiveness, persistence and dominance of promoters in Indian business imply that there is little scope for monitoring internal management by other large block holders. Hence, a disproportionate burden of governance has to fall on the board of directors of group companies. This is perhaps why the major governance reforms in India since their initiation in early 2000s have focused on good board governance. Board independence of listed companies as reflected in the requirement of the percentage of independent directors has been emphasized. While the agency problems of business groups have stayed the same or even aggravated, board regulations have exhibited the dynamism to address the potential agency costs, the chapter observes. Surajit Mazumdar in Chap. 5 focuses on the aspect of multi-entity structure and control in business group firms. He argues that, the business group structure in India can and does incorporate several companies/firms, which are neither publicly listed nor even individually large. So much so that several apparently stand-alone companies can also be parts of networks connecting them to other such companies/firms. The interconnections that link these several entities are, however, crucial inter alia to the exercise of control by business families over capital and wealth far in excess of what is legally owned by them. Concentrated control over assets as well as concentrated “ownership” of companies is the related outcome of this process, which provides an important reason for the resilience of the multi-entity group structure. His analysis shows that, the specific structure of the network of individual business groups and their participating entities changes over time in response to changing institutional contexts as well as due to its endogenous dynamics. Jitendra Mahakud and Gaurav Gupta in Chap. 6 explore the effect of business group affiliation on determination of corporate investment policy of the manufacturing companies in India. They find that the firm-specific variables like cash flow, Tobin’s q ratio, sales revenue, age of the company, financial leverage are the major determinants of corporate fixed investments. They also show that, companies affiliated to a business group invest more in the fixed assets than the stand-alone companies. Group affiliation reduces the impact of cash flow in determining corporate fixed investment. Their results indicate that financial distress plays a negative role in the

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determination of corporate investment. They also find that financial distress does not affect the investment-cash flow sensitivity of the affiliated firms in India. Ansgar Richter and Indrani Chakraborty in Chap. 7 analyze how performance of publicly listed firms in India is affected by the pattern of promoter ownership and highlight the specific role of business group affiliation in this respect. They have analyzed a sample of 4056 publicly quoted firms with promoter ownership in India during 2007–2013. They find that in group-affiliated firms, the level of promoter ownership has no effect on performance of firms, as measured by Tobin’s q and ROA. However, in stand-alone firms, the level of promoter ownership has a U-shaped relationship with Tobin’s q and no relationship with ROA. Moreover, group-affiliated firms show a lower performance than stand-alone firms. They have argued that, this happened due to the development of the capital market in post-reform India, which has greatly reduced the financing constraints for both group-affiliated and stand-alone firms. Jhuma Mukhopadhyay in Chap. 8 presents an account of the differences in the performance of group-affiliated firms and stand-alone firms in the post-reform period. This study is based on 14,274 BSE-listed manufacturing firms. She finds that groupaffiliated firms outperform the stand-alone firms. While examining the role of the factors responsible for better performance of affiliated firms, her study finds that both ownership opacity and internal financial capital are responsible for improved performance of group-affiliated firms. This refutes the institutional void theory. Corporate disclosures for protecting shareholders’ interests play an important role in corporate governance. In this context, related party transactions (RPTs) have emerged as one of the recurring areas of concern in developed as well as developing economies. These transactions are often diverse complex business transactions between a company and its key personnel—directors, or principal owners. Not only are they considered difficult to audit, abuse of such transactions can be detrimental to minority shareholder’s wealth. This is consistent with the conflict of interest hypothesis of Jensen and Meckling (1976). On the contrary, efficient contracting or efficient transactions hypothesis-related party transactions that are carried out at “arm’s length” can reduce transaction costs and further increase the profitability of the company thereby increasing the overall value to the shareholders. These conflicting hypotheses suggest that the effect of disclosing RPT is an empirical question that captures the trade-off between the management’s incentive to report competitive transactions thereby reducing the agency risk in share price and a source of entrenchment by management or insiders that increases the agency risk in share price. In Chap. 9, EktaSelarka and Subhra Choudhury investigate the relationship between disclosure of RPT and stock price crash risk faced by the Indian firms. Using a large sample of all the NSE-listed firms for the period 2005–2012, this study provides evidence that related party disclosure is associated with a decrease in the stock price crash risk faced by the firms. This finding is consistent with the view that information asymmetry increases crash risk. Further, the authors find that such decrease is observed more in the firms with higher risk. Rohit Azad in Chap. 10 addresses the question whether Minsky’s “Instability

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Hypothesis” does not hold good in the context of Indian corporate firms. To test the hypothesis, he takes a look at financial fragility (defined as inverse interest coverage ratio) and the debt-capital ratio as two widely accepted markers of financial fragility of the sector. Financial fragility is measured here as the ratio between interests owed to profits earned of the sector as a whole. Higher the ratio the more fragile the sector is because it shows that the companies (as a whole) are not even able to cover the interest owed to the lenders. The average ratios are considered for the entire corporate sector, in this study. He shows that, as the economy booms, overall leverage decreases in the Indian corporate firms. He further shows that the correlation coefficient with respect to GDP growth for both financial fragility and leverage is strongly negative, quite the opposite of what Minsky predicted. He argues that this result should not be surprising because this is the macroeconomic fallacy in Minsky’s argument. Then he carries out analyses of some specific industries and shows that some degree of instability was building up which would lead to financial fragility in the long run. This financial fragility is supposed to be generated by sudden decline in profitability of enterprises as a result of demand or supply shocks. The chapters in this volume present, in the Indian context, the complexity in the relationships between certain specific features of the business group firms and their performance, financial distress, stock price crash risk and governance. In this context, the important role played by public policy and the evolving laws and regulations in India are unraveled in greater detail in this volume. These chapters capture the nuances in this relationship as observed in India since independence till the postreform period. We feel that these chapters together form an important contribution to our knowledge on the nature and effects of these complex relationships in the dynamics of the corporate behavior in India.

References Almeida H, Wolfenzon D (2006) A theory of pyramidal ownership and family business groups. J Fin 61:2637–2681 Baek JS, Kang JK, Park KS (2004) Corporate Governance and firm value: evidence from the Korean financial crisis. J Finanl Econ 71:265–331 Bertrand M, Mehta P, Mullainathan S (2002) Ferreting out tunnelling: an application to Indian business groups. Quart J Econ 117:121–148 Chakraborty I (2013) Economic reforms, business groups and changing pattern of distribution of profitability across corporate firms in India: a semi-parametric analysis. Appl Finanl Econ 23(7):589–602 Chang H-J (2000) The hazard of moral hazard: untangling the Asian crisis. World Dev 28(4):775– 788 Corsetti G, Pesenti P, Roubini N (1999) What caused the Asian currency and financial crisis? Japan World Econ 11:305–373 Das Gupta C (2013) The tenacity of the hindu undivided family: gender, religion and tax concessions. Econ Pol Weekly 48(40):73–75 Faccio M (2006) Politically connected firms. Am Econ Rev 96(1):369–386 Fogel K (2006) Oligarchic family control, social economic outcomes, and the quality of government. J Intl Bus Stud 37:603–622

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Hillman AJ, Keim GD, Schuler D (2004) Corporate political activity: a review and research agenda. J Manage 30:837–857 Jadav AM, Reddy VN (2017) Indian business groups and their dominance in the Indian economy. Econ Pol Weekly 52(29) Jensen MC, Meckling WH (1976) Theory of the firm: managerial behavior, agency costs and ownership structure. J Fin Econ 3(4):305–360 Johnson S, La Porta R, Lopez-de-Silanes F, Shleifer A (2000) Tunneling. Am Econ Rev 90:22–27 Kali R, Sarkar J (2007) Diversification and tunneling: evidence from Indian business groups. Working Paper, Indira Gandhi Institute of Development Studies Khanna T, Palepu K (2000) Is group affiliation profitable in emerging markets? An analysis of diversified Indian business groups. The J Fin 55(2):867–891 Khanna T, Yafeh Y (2007) Business groups in emerging markets: Paragons or parasites? J of Econ Lit 45(2):331–372 Kim J (2008) Corporate lobbying revisited. Bus Pol 10(2):1–23 Kohli A (2006) Politics of economic growth in India, 1980–2005 Part I & Part II: the 1990s and beyond. Econ Pol Weekly April 1, 41(13):1251–1259 and April 8, 41(14): 1361–1370 Kohli A (2007) State, business, and economic growth in India. Stud Comp Intl Dev 42:87–114 Lawton T, McGuire S, Rajwani T (2012) Corporate political activity: A literature review and research agenda. Intl J Manage Rev 15(1):86–105 Mitra A, Pattanayak M (2013) Business groups, block holdings and firm value. Intl J Discl Gov 10(1):39–57 Mitton TA (2002) Cross-firm analysis of the impact of corporate governance on the East Asian financial crisis. J Finl Econ 64(2):215–241 Mody A, Nath A, Walton M (2011) Sources of corporate profits in India: Business dynamism or advantages of entrenchment? IMF Working paper No. WP/11/8 Morck R, Stangeland DA, Yeung B (2000) Inherited wealth, corporate control and economic growth: the Canadian diseas. In: Morck R (ed) Concentrated corporate ownership. University of Chicago Press, Chicago, pp 319–369 Morck R, Wolfenzon D, Yeung B (2005) Corporate governance, economic entrenchment and growth. J Econ Lit 43:657–722 Panagariya A (2008) India: the emerging giant. Oxford University Press, New York Richter A, Chakraborty I (2015) Promoter ownership and performance in publicly listed firms in India: does group affiliation matter? IDSK Occasional Paper, p 45 Rodrik D, Subramanian A (2004) From ‘Hindu Growth’ to productivity surge: the mystery of the Indian growth transition. Working Paper WP/04/77, International Monetary Fund Sarkar J (2010) Business groups in India. In: Ch 11 in Colpan AM, Hikino T, Linkoln JR (eds) The Oxford handbook of business groups. Oxford University Press, Oxford Shleifer A, Vishny RW (1993) Corruption. Quart J Econ 108(3):599–617 Shleifer A, Vishny RW (1994) Politicians and firms. Quart J Econ 109(4):995–1025 Singh A, Zammit A (2006) Corporate governance, crony capitalism and economic crises: should the US business model replace the Asian way of “doing business”? Corp Gove Intl Rev 14(4):220– 233 Stulz R (1999) Globalization of equity markets and the cost of capital. Unpublished working paper, Ohio State University Zattoni A, Pedersen T, Kumar V (2009) The performance of group-affiliated firms during institutional transition: a longitudinal study of Indian firms. Corp Gov Intl Rev 17(4):510–523

Chapter 2

The Regime of Capital Accumulation, the Hindu Undivided Family and the Business Group in Independent India Chirashree Das Gupta

Abstract The chapter addresses the issue of capital accumulation in the Hindu Undivided Family (HUF) and the business groups in India since independence. The organization of the ‘business house’ found legal sanction through multiple legislations spanning corporate and tax laws and forms the object of studies in ‘corporate governance’. The chapter argues that, it is the dual existence of the HUF as both a family and a firm that makes it distinct from all other institutional categories. It discusses the channels through which family control over the organizational structure of business groups and the ownership of wealth by the family generated through these structures are maintained. The interlocking of the caste Hindu patriarchal family with corporate governance institutions is formally embedded in law in India. It is the materiality of capital that forges the social entity of the family owned business group. This materiality is formally legally embedded in the seamless interlock of the firm and the family where the firm becomes the family in the case of the HUF. This spans state codification of Hindu family law, corporate governance laws and taxation laws. The chapter further argues that, it is capital in its material social role in the circuit of financial and capital flows, which drives the network of institutions that constitutes the ‘family owned business group’ in India legally. This is formally undergirded by caste, patriarchy and religion. Moreover, it shows that, this unique

This chapter is an extended and updated version of the publication of our paper Das Gupta and Gupta (2017) The Hindu Undivided Family in Independent India’s Corporate Governance and Tax Regime, SAMAJ 15. This earlier publication from 2017 is under a creative commons license. This chapter presents case studies in Sections 2.2 and 2.3 which are different from the ones in the 2017 article. The macro-level tax data analysed in Section 2.3 is updated till 2018 in this chapter. In the 2017 article, the data was upto 2012-13 in some cases and 2014-15 in other cases. However, the premise and the main arguments have significant overlap in both the publications. I am grateful to Mohit Gupta for his help with the tax data updation for this chapter. C. Das Gupta (B) Centre for the Study of Law and Governance, Jawaharlal Nehru University, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_2

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legal family/firm interlock is not available to Muslims, Christians, Parsis or Jews and hence constitutes a perverse legal privilege to the Hindu family.

2.1 Firm-Family Duality and the HUF in India In the mainstream of the discipline of economics, the two institutions that are taken as units of analysis are firms and households (with the household often conflated with family though the two words have entirely different meanings). For example, a household can consist of people living under one roof without any familial relationships. Similarly, a family maybe dispersed across multiple households. Moreover, a household can consist of people who have no familial relationships. These two units, namely the firm and the household are taken as mutually exclusive spheres of production and consumption respectively in mainstream economics despite the fact that households do produce and firms do consume. In this conception, the social becomes exogenous to the economic and is regarded as beyond the scope of economics. There is very little exploration of the link between the two even in institutional economics which does recognize the interplay between the social and the economic. Almost no literature exists on these inter-related units as institutions of capital accumulation. And yet business families inhabit our life world and the everyday. In the emerging literature on business groups in India, the entity of the ‘business group’ has found its place in institutional economics, economic sociology and the larger social science literature. But the familial basis of ownership and control of business groups remains an obscure area of study. The organisation of the ‘business house’ found legal sanction through multiple legislations spanning corporate and tax laws and form the object of studies in ‘corporate governance’. On the other hand, the institution of the ‘family’ has fallen in the ambit of study of ‘personal laws’. The first aspect is significant in establishing the institutional basis of concentration of capital combining the modalities of ownership and control. The second has implications for not only accumulation, investment and concentration of capital, but also tax avoidance and evasion (Das Gupta 2013). The relationship between these two aspects and the regimes of accumulation in independent India has been largely unexplored in the otherwise growing corpus of literature on the relation between the business group and ‘corporate governance’ and public policy. The Hindu Undivided Family (HUF) as an institution in India has a long history. It got legal recognition in colonial India in the late nineteenth century, but it was only with the promulgation of the Income Tax Act of 1922 that it got the status of a separate and distinct tax entity. The legal category of the HUF exists in the tax code since then and its inclusion in the code is based on a much longer history of recognition of customary law by the British colonial state in India. In the interpretation of the colonial state, the HUF represented a joint family that was held together by strong ties of kinship and comprised of a variety of joint property relations among the members. These relationships created blurred and porous boundaries between the cultural underpinnings of the family as a social entity and the commercial existence

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of the family as a trading entity. These porous boundaries were a complex function of marriage, lineage, patriarchal ties, and trade and business (Das Gupta and Gupta 2017). The colonial interpretation of the entity did not recognize the complex networks which resulted in the family as a business entity being governed by personal laws as against firms being defined by legal contracts. This had its roots in the colonial legal system which set a clear dividing line between the ‘public’ and the ‘private’. The ‘public’ side of it aimed at making an individual free of moral relations, and the law was meant to shape the individual’s relations freely in the market; while the personal side of it entrenched the denominational status based on caste, religion and family as basis for individual right (Das Gupta and Gupta 2017). This dual characteristic of the HUF shaped its legal status as a unit of business and taxation. It was recognized as a trading entity/ family firm as an income generating entity on the production side of the economy. But the arguments against it being taxed were premised on recognizing cultural ties, customary existence and the notion that the family preceded the firm, and that ‘family income’ was solely for the purpose of maintenance of the unit and fulfilling of customary obligations leading to the interpretation that the HUF is an income utilizing entity on the consumption side of the economy. This sharp exclusivity of definition inherent in the neoclassical conception of economic activities in the tight compartmentalization of production and consumption created the dilemma for the colonial state in deciding what exactly the HUF was at the time of the passing of the Income Tax Act of 1860 and 1886 (Das Gupta and Gupta 2017). Both the acts recognized the HUF as a variant of a legal person under the category of ‘individuals ‘(Birla 2008). Finally in the debate on the Super Tax Bill of 1917, the HUF was proposed to be recognized as a distinct category for taxation to overcome the problem of having to negotiate the dual characteristics of being a family and a business entity. This interpretation led to the recognition of the HUF as a separate tax entity which was subsequently incorporated into the Income tax Act 1922 (Newbigin 2013). It is this dual existence of the HUF as both a family and a firm that makes it distinctive from all other institutional categories as we shall see in the rest of this chapter. The independent Indian state took the HUF as a distinct category in its legal framework and thus avoiding any engagement with the ‘duality’ question allowing the HUF a seamless transition as a legal entity from colonial to independent India. It was in the first decade after independence with the state’s encoding of Hindu customary and personal law that the HUF was legally sanctified as originating in state code and then integrated into the Indian corporate governance and taxation system. Thus the HUF’s sanctification in the state code of Hindu law is the only major departure in its status after independence as compared to the colonial period (Das Gupta and Gupta 2017). Family owned business groups in India comprise of a plethora of corporate bodies spanning joint stock companies (public and private limited), partnership firms, trusts and other body incorporates and limited liability partnerships. Each of these vehicles of corporate governance are regulated by different pieces of legislations namely

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the Companies Act 2013; the Indian Partnership Act 1932, the Societies Registration Act 1860 and the Limited Liability Partnership Act 2008 respectively. Despite these different pieces of legislation regulating these different corporate entities, interlocking directorships and inter-locking shareholdings across these entities constitute these into the social entity of the business group in India (Das Gupta 2013). The top twenty two business houses in India through this system of interlocks directly controlled 25% of gross capital formation in the Indian economy in 1951. By 1990, this accounted for 28% of gross capital formation in India and is estimated to be at least 40% today. The extent of this control is however exercised by less than 1% actual investment by the business group (Das Gupta 2016). The key houses of business, both old and new, have found ways to maintain control over decision making through the institutional structure of the family run business house (Das Gupta 2010). There are two distinct channels through which family control over the organizational structure of business groups and the ownership of wealth by the family generated through these structures are maintained. The first has to do with the legal provisions of ‘corporate governance’ structures which facilitate the optimum mix of various forms of registered companies like partnerships, private limited companies, unregistered and registered public limited companies, and limited liability partnerships under the umbrella business group through interlocking share-holdings and directorships. These are done within the enabling legal provisions of the Indian Partnerships Act of 1932, the Companies Act of 1956 and 2013 and the Limited Liability Partnership Act of 2008. Apart from risk spreading, this structure had also ensured avenue to escape the minimal restrictions on expansion under Monopolies and Restrictive Trade Practices after 1973 till it was repealed after liberalization. It was also important for labor deployment and control with employers often making sure that each company only had less than seven employees and pre-empting any possibility of trade union formation under the stipulations of the Trade Union Act of 1926. The second is through the legal sanctity given to the category of the Hindu Undivided Family (HUF) by interweaving it into corporate governance structures, family laws and the tax codes. Interlocked firms and families are the legal structure in which capital accumulation is institutionally embedded in India. It may also be noted that the first level of the firmfamily interlock is germaine to capitalist firms universally i.e. individual members of families own and control shares. But in India, the HUF interlock with firms is unique and specific in not only maintaining control of the family, but this privilege as a legal entity is only endowed to Hindus as defined in the state’s codification of Hindu personal and family law ie a Hindu is anyone who is not Muslim, Parsi, Christian or Jew. After defining the HUF through the codification of personal laws in 1955–56, the state then took the next step to perpetuate the ‘Hindu Undivided Family’ (HUF) as an entity recognized by the Wealth Tax Act 1957 and Section 2 of the Income Tax Act 1961 as a distinct unit of taxation with grant of tax avoidance facilities on ‘family income’ with higher exemptions and lower tax rates compared to other categories of assesses. The tax rates for the HUF is the same as that of individuals since the intervention of the Wanchoo Committee and the K N Raj Committee but HUFs were subject to a lower rate of taxation than individuals before these interventions.

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Social science has largely not engaged with this socio-legal entity. In corporate law, tax law and personal law—the three spaces it inhabits—it has been largely regarded as a ‘loophole’ that is incongruent with ‘modern’ corporate governance and taxation structures. It is often referred to as a remnant from the archaic which does not serve any purpose in contemporary modes of capital accumulation. The women’s movement in India that has had the closest engagement with this structure has often associated it with feudal structures of land and property holdings. Its implications on capital accumulation in the ‘modern’ sectors have not been studied at all. This paper, based on analysis of macroeconomic data and case studies extracted from a comprehensive primary research on 150 family owned business groups in India is an attempt to interrogate such propositions and to arrive at a comprehensive delineation of the role of the HUF in the capital accumulation regime in independent India. The paper is divided into three sections. Section 2.1 above has elucidated the process through which the HUF was institutionally embedded into the state’s codification of the Hindu personal and family law. Section 2.2 analyses the institutional embedding of the HUF in corporate governance structures. Section 2.3 dwells on installation and use of the HUF in tax structures and the role it plays as a vital institution in tax avoidance processes. The three sections together show the critical role the HUF plays in the circuits of capital accumulation in India.

2.2 Institutional Embedding of the HUF in Corporate Governance Structures In our study of 150 family owned business groups in India carried out in two phases (2003–05 and 2008–11), except for the two groups which were not of Hindu origin in our survey, all business groups had Hindu Undivided Family (HUF) accounts. On an average, each group controlled directly and indirectly about 47 companies. Each business group had on an average three to four holding companies along with one to three flagship companies. In these companies, the Karta of the family along with other members held shares as individuals. The next biggest single share-holding in these companies was by HUFs belonging to the family. At least two family members in every case were directors of these companies. These companies in turn owned shares of other public limited, private limited and partnership firms which they controlled. In such firms and companies, family members and close associates from other business families are directors. In addition, these groups control trusts governed by the Societies Registration Act 1860 (as we shall see later) and other related legislation (Table 2.1). This forms the formal structure of ownership and control through which all activities related to capital accumulation by business families is controlled. In 35.3% of the groups surveyed, stocks in group companies were not held by HUFs in publicly listed companies, but were held in the ‘private limited’ companies. The Kartas of the HUF or other HUF members however held stocks in the publicly listed companies

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Table 2.1 Summary of the survey on HUFs and business groups Number of business families surveyed Number of firms affiliated to business groups which were analyzed for institutional interlocks Average number of companies/firms in a family owned/controlled business group

150 7500 47

Average number of HUFs found to be interlocked in each business groups

9

Average number of trusts/registered societies found to be interlocked with each business group

4

Number of detailed case studies of family owned business groups

25

Number of members of business families interviewed as part of case studies

300

Number of managers of firms interviewed as part of case studies

300

Number of employees who were not managers interviewed as part of case studies

200

Source Author’s survey of 150 business groups

in 61.3% of the groups surveyed. Thus the payouts to the HUF as well as to the individual who is part of an HUF is simultaneously maintained. At the same time, the HUF can hold other property e.g. houses, cash, gold, share certificates, fixed deposits which would not be considered in the asset accounting of the business group. The income and wealth holdings in HUF do not get counted in the business group’s ownership and control of assets. This interlocking structure of firms and families serves multiple purposes of which we will illustrate two major uses: 1. Family control over the circuits of capital within the business group 2. Tax avoidance. In this section, we focus on the first purpose. Apart from the HUF being a vehicle of tax avoidance (illustrated in the subsequent section), both ‘old’ and ‘new’ capitalist business houses of Hindu origin use the provision of HUF to consolidate family holdings and ensure the control of capital within the family through transactions between the HUF and individuals within the HUF who held key positions in the share-holding and managerial patterns of the companies within the fold of the business house through interlocking directorships and share-holding. To illustrate the modalities of family control over the circuits of capital within the business group, we present another case study from our survey. Patriarch A from business family 1 is married to B from business family 2. They have three sons C, D and E and one daughter F. C, D and E have a son each named M, N and O. Daughter F is married to G into business family 3. Sons C, D and E are married to H, I and J and from business families 4, 5 and 6. The HUFs created from these alliances in Family 1 are: 1. 2. 3. 4. 5. 6.

HUF1 (A—karta, C, D and E coparcenaries, B member): HUF2 (C—karta, H member) HUF3 (D—karta, I member) HUF 4 (E—karta, J member) HUF 5 (A—karta, C—coparcenary, B and H member) HUF 6 (A—karta, D—coparcenary, B and I member)

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7. 8. 9. 10.

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HUF 7 (A—karta, E—coparcenary, B and J member) HUF 8 (C—karta, M coparcenery (minor with C as guardian) HUF 9 (D—karta, N coparcenary (minor with D as guardian) HUF 10 (E—karta, O coparcenary (minor with E as guardian)

Thus 10 HUFs can be operated by a single family because the law entails the provision that any Hindu male can start a new ‘Hindu Undivided Family’ as long as he is married. Even as families went nuclear, the ‘HUF’ could be perpetuated as a legal entity as each nuclear family marked the beginning of a new ‘HUF’ without requiring the dissolution of earlier HUFs including the same family members. Similar HUFs exist in families 2, 3, 4, 5 and 6. Family 1 has two flagship companies—MLX Ltd and MLY Ltd. Six percent of shares in MLX Ltd are held by A, B, C, D and E. Another five percent shares are owned between HUFs 1, 2 3 and 4. Similarly, seven percent shares in MLY Ltd are held by A, C D and E. Another four percent is held by HUFs 5, 6, 7 and 8. Eight other group companies together hold twelve percent shares of MLX Ltd. Nine different group companies hold twelve percent share of MLY Ltd. There are three other subsidiary/ holding companies in the group. These hold shares in twelve other group companies. HUFs 9 and 10 hold two percent shares in all twelve of these group companies. Two group companies along with A, B, C, D, E, F, G, H, I and J hold shares in two trusts named after A’s grandfather, and father respectively. These trusts own shares of eight group companies. HUFs belonging to families 2, 3, 4 and 5 have shares in eight group companies. The daughter, son-in-law and the three daughters-in-law own shares as individuals in five corporate entities in which two are partnerships and three are companies. Thus individuals, HUFS, firms/companies and trusts form multiple level of overlapping interlocks to control 34 firms/companies and two trusts, even though each of these entities are governed by different corporate governance laws as we have shown earlier. A, the patriarch is a director in eight companies, The sons C, D and E and the son-in-law G in six each, the daughter F in three, four members each from families 2, 3, 4 and 5 in two each. All the women in the family are involved as sleeping directors in group companies as well as active management of the trusts in position of executive authority. Had there been no HUF provision, individual family members would need to own a much larger proportion of shares to exert family control over the constituent firms/companies in the business group. But with the HUFs, a much larger sphere of control can be exercised with minimal investment of family wealth. This business group owned four large and five medium sized factories and three small scale enterprises spread over five states in India. Out of these, four were owned by public limited companies, five were owned by private limited companies, two by HUFs and one by a partnership. These factories were integrated into the global value chain of a range of manufacturing goods in consumables.

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Eighteen other corporate entities in the group were shown to be invested in a nonbanking finance company, hotels, trading, property dealing and leasing and entertainment. The trusts ran for-profit schools along with running temples, two hospitals and an orphanage. The total investment by the families and individuals in the 34 corporate entities it exerts control over is 1.44% of the total investments. But the family effectively through combination of individual members, interlocked companies and HUFs control 70% of the share-holding and through inter-locking directorships, 90% of the board of management. On an average, 26 out of the 34 corporate entities reported losses in the previous four years. With asset and income transfers within group companies and HUFs (through related party transactions), profit and loss accounting is spread across business groups to declare the minimum level of profits once again to avoid taxation. A similar case study of the largest business group in India by Naz (2016), shows that around 64 out of 88 group companies, reported loss in two consecutive years. It must be noted here that such related party transactions are by the law to be approved by the Board of the company. Given the interlock between family members on the board, such transactions are blessed by the legal sanction of the corporate governance structure interlocked with the family. The HUF also exists legally in tax law independent of these interlocked entities. For example, land for eight of the factories is owned by four different HUFs of family 1 and are shown to have been leased to the company owning the factory or enterprise. The transfer of lease income is to the HUF for which taxation is at par with an individual. However, the HUF is a corporate entity as we shall see in the next section and hence this is yet another way in which corporate tax exemption on income is being perpetuated through the legal regime of corporate governance in India. Our interviews with the family members of this family owned business group revealed certain remarkable aspects of the firm/family interlock. All the men and women had been married through alliances brokered by the family. Early marriages were the norm. There was significant resistance to the idea of marriages of choice. All marriage alliances were based on caste rules of endogamy and exogamy along with considerations of class status. In another case study, we had found that while marriages across ethnicities were considered ‘normal’, caste and class barriers were rigid. Thus families founded on the basis of caste rules and patriarchy are the defining features of the business family in India. The materiality of capital forges the social entity of the family owned business group which is formally legally embedded in the seamless interlock of the firm and the family. This spans state codification of Hindu family law, corporate governance laws and taxation laws. This unique legal family/firm interlock is only available to Hindus. It is not available to Muslims, Christians, Parsis or Jews and hence constitutes a perverse legal privilege to the Hindu family. The caste Hindu patriarchal family bound by son preference is an imperative of social reproduction of institutional structures of accumulation in India. In the next section we shall see how this son preference is incentivized by institutions of taxation. It is capital in its material

2 The Regime of Capital Accumulation, the Hindu Undivided Family …

21

social role in the circuit of financial and capital flows that drives the network of institutions that constitute the ‘family owned business group’ in India undergirded by caste, patriarchy and religion (Das Gupta and Gupta 2017).

2.3 HUF as a Vehicle of Tax Avoidance We start with the distinction between statutory and effective taxation rates. There is difference between the statutory rates which are announced every year by modification of the Finance Act and what finally transcends into the actual payments as taxes by income tax payers. These actual payments as percentage of declared income are called the effective tax rates. Statutory rates are the ones prescribed by law, the effective tax rates are the realized average tax rates (Das Gupta and Gupta 2017). Let us go back to our case study in the earlier section. Patriarch A from business family 1 is married to B from business family 2. They have three sons C, D and E and one daughter F. C, D and E have a son each named M, N and O. Daughter F is married to G into business family 3. Sons C, D and E are married to H, I and J and from business families 4, 5 and 6. The HUFs created from these alliances in Family 1 are: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

HUF1 (A—karta, C, D and E coparcenaries, B member): HUF2 (C—karta, H member) HUF3 (D—karta, I member) HUF 4 (E—karta, J member) HUF 5 (A—karta, C—coparcenary, B and H member) HUF 6 (A—karta, D—coparcenary, B and I member) HUF 7 (A—karta, E—coparcenary, B and J member) HUF 8 (C—karta, M coparcenery (minor with C as guardian) HUF 9 (D—karta, N coparcenary (minor with D as guardian) HUF 10 (E—karta, O coparcenary (minor with E as guardian)

Let the annual taxable income stream from the companies MLX Ltd and MLY Ltd for A, C, D and E be Rs 20 lakhs each. In the absence of any HUF provisions, A, C, D and E would have to each pay Rs 412,500/—as income tax as per taxation rates for Financial Year 2018–19 by application of statutory rates (Table 2.2). The effective taxation rate is 20.625% in this scenario. However, A, C, D and E can use the ten HUFs effectively among themselves and distribute the income across their four individual tax accounts and the ten HUFs (Table 2.3) using the provisions of existing income tax laws and the four acts codifying Hindu property laws. In such a scenario, the total tax liability would be only Rs 225,000/—each for A, C, D and E. The effective taxation rate has been almost halved to 11.25% in the second scenario by using the HUFs. With separate application of other exemption possibilities under the Income Tax Act, the actual tax liability can be brought down to much further even for much larger sums of income from multiple sources. Similar use of the HUF can be made

22

C. Das Gupta

Table 2.2 Effective tax liability in the absence of HUF—scenario 1 Tax entity

Income reported from MLX Ltd and MLY Ltd (Rs)

Tax to be paid at 2018–19 rates (Rs)

A

2,000,000

412,500

C

2,000,000

412,500

D

2,000,000

412,500

E

2,000,000

412,500

Total

8,000,000

1,650,000

Source Author’s calculations based on case study

Table 2.3 Effective tax liability with the use of HUF—scenario 2 Tax entity

Income reported from MLX Ltd and MLY Ltd (Rs)

Tax to be paid at 2018–19 rates (Rs)

A

1,375,000

225,000

C

1,375,000

225,000

D

1,375,000

225,000

E

1,375,000

225,000

HUF1

250,000

0

HUF2

250,000

0

HUF3

250,000

0

HUF4

250,000

0

HUF5

250,000

0

HUF6

250,000

0

HUF7

250,000

0

HUF8

250,000

0

HUF9

250,000

0

HUF10

250,000

0

Total

8,000,000

900,000

Source Author’s calculations based on case study

to circumvent wealth and property tax. Moreover, if any member were to draw an income from the coiffeur of ‘family income’ accumulated in the HUF, such income would be exempt from taxation by virtue of being the higher cost of maintenance of the ‘undivided family’. Thus it must be noted that the use of HUF for tax avoidance is perfectly legal in India. If A had four married sons with a male child each and no daughter, he would be able to form two additional HUFs which could be used to reduce tax liabilities of family members further. If any of the sons do not get married, then the possibility of forming the additional HUFs reduces. Thus son preference and hetero-normative marriages in every generation, bound by caste and religious rules as per the state’s

2 The Regime of Capital Accumulation, the Hindu Undivided Family …

23

Hindu code, have a very material incentive in the form of the HUF tax provisions in India. Figure 2.1 shows annual average effective taxation rates (ETR) of individuals, HUFs and all other assessees (which consist of different forms of body incorporates or corporate entities—firm, companies, societies and trusts etc.). From 1954–55 to 1998–99, the ETR of individuals were the lowest, the ETRs of corporate entities were the highest while the ETR of HUF was between the two. Also, the ETR of all entities increased between 1973 and 1993. There were several reasons for this. First, there was abolition of higher exemptions and lower tax rates to HUF as compared to individuals. Second, there was the promulgation of the Monopolies and Restrictive Trades Practices (MRTP) Act in 1971 which recognized the business group as a whole as the unit of organization of capital and put in restrictions on interlocking shareholdings and directorships. Third, the ETRs of HUFs increased significantly in the same period with the abolition of HUF privileges in land and other property holdings (but not corporate holdings which come under the purview of the central government) in Tamil Nadu, Kerala, Andhra Pradesh and Maharashtra. The decline in ETRs of corporate after the mid-1980s is explained by the dilution of the MRTP Act and its subsequent repeal. The ETRs show a sharp decline in 1998–99 and 1999–2000 after which the CBDT stopped releasing data. Compared to the pre-1991 levels, ETRs of all tax categories have declined. The recent data that has been released since 2012–13 to 2017–18 shows a significant decline in the ETR of individuals. But the steepest decline is recorded by the ETR of HUFs in this period. Figures 2.1 and 2.2 together show that HUFs have paid the lowest rates of ETR since 1956 in the period 2012–13 to 2017–18. 45.00

INDIVIDUALS

HUF

ALL OTHER ASSESSES (EXCEPT INDIVIDUALS AND HUF)

40.00 35.00 30.00 20.00 15.00 10.00 5.00 2016-17

2014-15

2012-13

1996-97

1998-99

1994-95

1990-91

1992-93

1988-89

1986-87

1984-85

1980-81

1982-83

1978-79

1976-77

1974-75

1971-72

1968-69

1966-67

1964-65

1962-63

1960-61

1958-59

1956-57

0.00 1954-55

Effective Tax Rate in Percentage

25.00

Years

Fig. 2.1 Annual effective tax rate for HUF, individuals and all other assesses (1954–55 to 1999– 2000; 2012–13 to 2017–18). Source All India Income Tax Statistics Released by Central Board of Direct Taxes for Data up to 1999–2000 and Income Tax Data from website of Central Board of Direct Taxes for Data from 2012–2018. Note Disaggregated Data for Various Assesses is not available for the period 2000–2011

35.00 30.00

25.00 20.00 15.00 10.00

17.33 17.74 17.41 15.97 13.85 14.12 13.56 15.74 14.78 14.27 15.12 13.62 16.91 18.57 17.35 18.68 22.31 20.50 23.53 23.84 23.90 24.42 24.15 23.25 24.99 24.99 26.05 23.98 31.85 25.68 23.00 23.58 23.78 19.98 19.84 24.78 24.76 25.57 27.55 18.09 16.35 13.05 16.78 11.71 8.65 8.15 8.67 8.68 9.22 10.08

C. Das Gupta

ETR for HUF

5.00 2016-17

2014-15

1998-99

2012-13

1994-95

1996-97

1992-93

1990-91

1988-89

1984-85

1986-87

1982-83

1980-81

1976-77

1978-79

1974-75

1971-72

1968-69

1964-65

1966-67

1962-63

1960-61

1958-59

1954-55

0.00 1956-57

Effective Tax Rate in Percentage

24

Years

Fig. 2.2 Annual effective tax rates of HUFs (1954–55 to 1999–2000; 2012–13 to 2017–18). Source All India Income Tax Statistics Released by Central Board of Direct Taxes for Data up to 1999–2000 and Income Tax Data from website of Central Board of Direct Taxes for Data from 2012–2018. Note Disaggregated Data for Various Assesses is not available for the period 2000–2011

However, the ETRs across time do not tell us about the extent of regressiveness of the direct income tax in India. Figure 2.3 shows that the effective tax rates of firms and companies decrease as size of income increases. For individuals the trend of taxation is initially progressive but becomes regressive at the top range for incomes above Rs 50 lakhs. The same trend is evident for the HUF but with two significant features. First, at the bottom end, up to an income below Rs 5 lakhs, the effective rate of taxation of HUFs is consistently regressive. Second, the ETRs of HUFS is significantly less than individual tax assessees for every level of income. Third, for incomes above Rs 50 lakhs, ETRs of HUF again turn regressive. An analysis of the sources of incomes for various categories of tax assessees for the period 2012–18 (the years for which this data is available) is presented in Tables 2.4 and 2.5. Individuals are the only category of income earners who earn an income for salary. HUF income accrues from business income, short and long term capital gains, house property income and interest income. There is no salary income reported by HUFs. In fact the composition of the HUF income is similar to income composition of firms, companies and other body incorporates and very different from the composition of individual incomes in which salary income constitutes around 54% of the income. Thus the HUF is similar to a corporate entity with the additional characteristic that around 9% of its income comes from house property while this share is less than 4% for firms and companies. But, it gets away with exemptions claiming to be a ‘family’ utilizing income for maintenance treated at par with an ‘individual’ tax payer and pays the lowest rates of income tax as demonstrated earlier. Thus the effective tax paid by the HUF is much lesser than corporate entities of business even though its income structure is similar to corporate entities as we have shown earlier.

2 The Regime of Capital Accumulation, the Hindu Undivided Family …

25

90.00

Individuals

HUF

FIRMS AND COMPANIES

OTHERS

Effective Tax Rate in Percentage

80.00

70.00 60.00 50.00 40.00 30.00 20.00 10.00

>500,00,00,000

>100,00,00,000 and 50,00,00,000 and 5,00,00,000 and 25,00,00,000 and 10,00,00,000 and 1,00,00,000 and 50,00,000 and 25,00,000 and 20,00,000 and 10,00,000 and 15,00,000 and 9,50,000 and 5,50,000 and 5,00,000 and 4,50,000 and 4,00,000 and 3,50,000 and 2,50,000 and 1), there is an incentive to invest because expected earnings from invested assets are high. We, therefore, estimate Tobin’s Q for RBI sample companies. Construction of Market Value and Replacement Cost of RBI Sample Companies Items reported in the balance sheets of companies, particularly those relating to longterm liabilities and fixed assets are reported as per their historical value. Net worth, as reported in the balance sheet of a company, need not reflect market value of equity of that company. While one may argue that a company would have invested the amount as shown in balance sheet, book value of equity should be taken as such. However, investors’ expectation from the company is based on its current market value, which depends upon the expected stream of earnings they are likely to get from the invested assets. This determines the enterprise value and so we need to find out market value of any item under consideration. In line with this rationale, market value of long-term liabilities as well as replacement cost of RBI sample companies had been worked out as follows. Market value of equity of a company is its market capitalisation (MK) defined as number of equity shares (N) times current market price of a share (P), that is, MK = N*P. Information on MK and N of samples companies is not available from RBI studies. To convert book value of equity capital into market value, we rely on price to earnings (P/E) ratio, where earnings represent earnings per share (EPS) defined as PAT divided by N.

3 Corporate Response to Public Policy Changes: Some Intriguing Aspects

47

Let P/E ratio be denoted by X and so X = P/EPS Therefore, X = P/(PAT /N) or X = (P*N)/PAT Rewriting it, we have X ∗ PAT = P ∗ N where P*N is the market capitalisation (MK). To arrive at the MK of sample companies, we need their respective PAT and P/E ratio (or X). While PAT of RBI sample companies is available, P/E ratio is not, for which we consider P/E ratio of NSE 500 companies as a proxy. For its studies, RBI covers more than 3,000 companies and so it is believed that P/E ratio of NSE 500 companies7 would better represent P/E ratio of a large number of companies. Using this, we first estimate the MK of RBI sample companies, as: MKRBI Sample = PATRBI Sample ∗ P/E Ratio of NSE 500 In order to arrive at the market value RBI sample companies, we add their preferred capital and debt. That is, Market ValueRBI Sample = MKRBI Sample + Preferred CapitalRBI Sample + DebtRBI Sample Since preferred capital and corporate debts are not actively traded, we have considered their book value. Replacement cost of assets basically refers to current value of fixed assets and inventory. Fixed assets are acquired at different vintage points and, because companies follow the cost principle of accounting, these assets are reported in balance sheet in terms of their purchase or historic price. To arrive at their replacement value, historic price of assets needs to be converted into their respective current value—a process widely known as capital stock estimation. By following the perpetual inventory method (PIM), attempts have been made to build up capital stock at the firm level as well as at the aggregate level.8 Since RBI studies do not provide firm wise information and they are sample based, it is not feasible to follow PIM. Thus, to arrive at the replacement cost of asset we follow an indirect approach. In the NAS, net fixed capital stock (NFCS) and net fixed capital formation (NFCF) data are available for PCS as a whole. Given that capital formation is a counterpart of capital stock, we assume a relationship between NFCF and NFCS. Thus, the ratio of NFCSPCS to NFCFPCS is considered as the factor9 for arriving at the replacement cost of assets of RBI sample companies. The changes in net fixed assets (NFA),

7

They include financial and government companies as well. P/E ratio is as of financial year end, collected from the website of National Stock Exchange (NSE) (www.nseindia.com). 8 For firm level, see Rajakumar (2005); and for aggregate level, see Central Statistical Organisation (2012). 9 This is based on data extracted from EPWRF India Time Series.

48

J. D. Rajakumar

Table 3.9 Trends in Tobin Q

Types of companies

Period I

Period II

Period III

NGNF PLC

1.0

2.0

1.6

NGNF PTC

1.0

2.0

1.4

All companies

1.0

2.0

1.5

FDI companies

2.3

2.5

1.6

Note 1. NGFC PLC refers to non-government non-financial public limited companies 2. NGFC PTC refers to non-government non-financial private limited companies 3. All companies includes NGFC PLC and NGFC PTC 4. FDI companies refers to foreign direct investment companies Source Author’s calculations based on RBI’s studies of company finances

reported in the combined balance sheet of RBI studies, basically represent NFCF at the sample level.10 We have taken the book value (BV) of inventory as part of the replacement cost. We assume here that firms follow First-in First-out (FIFO) approach to managing inventories and so their book value may not significantly change between one year and the succeeding year. Replacement cost of RBI sample companies has thus been worked out as   Replacement CostRBI Sample = Change in NFARBI Sample ∗ (NFCSPCS /NFCFPCS ) + BV of InventoryRBI Sample Using the estimates of market value and replacement cost, Tobin’s Q has been worked out for RBI sample companies (see Table 3.9). A few observations are in order. Firstly, the period averages of Tobin’s Q remained more than one for all categories of companies in all periods. Secondly, the movements in Tobin’s Q are in line with that of the economy’s growth; that is, Period II reportedly has a higher Tobin’s Q, followed by Period III and then Period I. Finally, Tobin’s Q has remained higher in Period II and III compared to Period I. As noted above, if Tobin’s Q is higher than 1, it would mean that market value is better in relation to replacement cost and this would bolster investment activities. Tobin’s Q remained greater than 1 throughout and this indicates that stock market valuation drives corporate investment activities.11 It is rather not surprising given the 10

For estimating capital formation, CSO considers only reproducible tangible assets such as buildings, machinery and equipment and it excludes non-reproducible tangibles assets such as land (CSO, 2012). In the balance sheets, companies report land as part of their fixed assets and we have retained it as part of NFA, as it is very much part of firms replacement cost. 11 Following a similar approach and using RBI’s studies of NGNF PLC for the period 2005–06 to 2012–13, Rajakumar (2014d) estimated Tobin’s Q for these companies and found the correlation coefficient between Tobin’s Q and growth rate of gross capital formation of PCS to be 0.890 and between Tobin’s Q and growth rate of GFCF of PCS to be 0.879.

3 Corporate Response to Public Policy Changes: Some Intriguing Aspects

49

overwhelming reliance of companies on own resources, that is shareholders’ fund, over the years. This also reflects an increased share of profit in corporate NVA as well; profit after tax accrues to shareholders/owners of companies.

3.5 Trends in Incidence of Corporate Tax Reducing corporate direct tax structure and rationalization of tax incentives were integral parts of economic reforms. For a long time, companies in India faced relatively high level of direct tax structure; for instance, statutory tax rate (STR) faced by domestic companies was as high as 59.13% in 1980–81, though it was gradually reduced to 54.0% in 1989–90 (Rajakumar 2014c). Taking cognizance of the tax rate spread of 24 such countries, the Tax Reform Committee (Chariman: Raja J. Chelliah) considered corporate tax rate of 40% as reasonable, though it was of the opinion that 35% would be attractive to investors (Government of India 1992, p. 11). In line with the Committee’s recommendation, corporate STR has been gradually reduced since then. Simultaneously, with reduction in corporate STR, several erstwhile tax concessions were discontinued, but a few items such as depreciation allowance and tax holidays continued. Incidence of corporate tax can be measured by effective tax rate (ETR), which is tax provisions expressed as percentage of PBT. The ETR as percentage of STR reveals the extent of tax incidence compared to the government’s stipulated tax rates. Higher the ratio, larger is the tax incidence. The period averages of STR stood at 43.3, 34.9 and 33.3%, respectively, for all the three periods.12 Thus, compared to Period I, the STR stood lesser by 8.4 percentage points in Period II. In line with this, the period averages of ETR of all sample set of companies have come down (Table 3.10). The reduction in the ETR in Period II is by 4.7 percentage points in FDI companies, by 2.8 percentage points in NGNF PLC and by 0.8 percentage points among NGNF PTC. The declining trend continued in Period III as well, although by a small margin of 0.8 percentage points in the case of NGNF PLC and by 1.8 percentage points among FDI companies and by 2.9 percentage points in case of NGNF PTC. However, the ETR as percentage of STR showed a sharp rise in Period II. Despite a marginal fall in the ETR as percentage of STR in Period III compared to Period II in NGNF PTC and FDI companies, the level remained higher in Period III compared to Period I. This suggests that incidence of corporate tax has gone up over the years. In other words, the reduction in STR has been positively responded by corporates and this also reflected in tax provisions as 12

Under Income Tax Act, any company incorporated in India is a domestic company, whether it has a foreign holding or not. A unit set up by a foreign company in India can well be a subsidiary which is incorporated in India, in which case it would be considered a domestic company. The STRs have been collected from Finance Bill, accompanying Union Budget of Government of India, of the relevant financial years. The STR refers to mandatory Corporate Tax Rate. Additionally, it includes Surcharge, Education Cess, and Secondary and Higher Education Cess, as they were stipulated from time to time.

50

J. D. Rajakumar

Table 3.10 Trends in effective tax rate (in %) Types of companies

Period I

Period II

Period III

Effective tax rate

Period I

Period II

Period III

Effective tax rate as % of statutory tax rate

NGNF PLC

28.8

26.0

25.2

69.0

74.5

76.1

NGNF PTC

35.1

34.3

31.4

82.0

98.6

95.2

All companies

28.9

26.3

25.2

69.2

75.4

76.0

FDI companies

35.4

30.7

28.9

82.5

87.9

87.1

Note 1. NGFC PLC refers to non-government non-financial public limited companies 2. NGFC PTC refers to non-government non-financial private limited companies 3. All companies includes NGFC PLC and NGFC PTC 4. FDI companies refers to foreign direct investment companies Source Author’s calculations based on RBI’s studies of company finances

percentage of these companies’ respective NVA remaining higher in Period II and III compared to Period I (Table 3.6). Tax Avoidance Declines A related question here with whether reduction in STR has been accompanied by a reduction in the tax avoidance practices by companies. Broadly, there are two ways of avoiding tax, one, by adjusting capital (financing) structure and, two, by benefiting from several tax relief measures in force from time to time in order to keep up the tempo of corporate investment.13 In studies of capital structure, it is widely argued that firms opt for debt financing because interest expenses were allowed to be deducted from current revenue and to the extent debt financing helps to shield their income (Fama and Miller 1972). The reasoning is that a large amount of interest outgo would erode the PBT, the basis for computing tax liabilities, and so heavy interest payments would reduce tax liabilities of companies. In the previous section, we had observed that debt as percentage of total liabilities had considerably come down over the years. Side by side, the interest payments as percentage of EBIT also showed a sharp decline in Period II, though showed a marginal rise (Table 3.11). For all companies together, interest payments to EBIT dropped from 52.3% in Period I to 21.9% in Period II, though it rose thereafter to 28.7% in Period III. Compared to Period I, interest burden remained considerably lower; which is largely an outcome of reduction in corporate reliance on borrowings. The extent of interest outgo depends upon cost of borrowing and reliance on debt financing. Cost of borrowing can be measured by relating interest expenses to total borrowing. That is, Nominal cost of debt = Interest expense / Borrowings ∗ 100 13

Although companies in India faced high direct tax rates, they were given several tax reliefs and concessions, mostly linked to investment, such as depreciation allowance, investment allowance, tax holidays, loss carry forward, etc., so as to facilitate generation of funds internally. For further details, see Rajakumar (2009).

3 Corporate Response to Public Policy Changes: Some Intriguing Aspects Table 3.11 Trends in interest payments as % of earnings before interest and taxes

51

Types of companies

Period I

Period II

Period III

NGNF PLC

52.5

21.9

28.9

NGNF PTC

54.6

22.0

30.4

All companies

52.3

21.9

28.7

FDI companies

31.7

14.1

24.7

Note 1. NGFC PLC refers to non-government non-financial public limited companies 2. NGFC PTC refers to non-government non-financial private limited companies 3. All companies includes NGFC PLC and NGFC PTC 4. FDI companies refers to foreign direct investment companies Source Author’s calculations based on RBI’s studies of company finances

Although it is common to consider nominal cost of debt, what matters is netof-corporation-tax cost of debt (Patil 1979). That is, effective cost of debt which is arrived at after netting out tax benefits arising out of interest deductibility from interest payment. That is, Effective cost of debt = (Interest expense − (STR ∗ Interest expense)) / Borrowings ∗ 100

If cost of borrowing rises, debt becomes costlier, which is likely to reduce the importance of debt vis-à-vis own resources. As shown in Table 3.12, nominal cost of debt of companies across the board has substantially come down in Period II, when borrowings to total liabilities also have gone down. During the same period, effective cost of borrowing has also gone down. Both nominal and effective cost of borrowing registered some increase in Period III, although the level is considerably lower compared to Period I. More importantly, the spread between nominal and effective cost of borrowing has narrowed down substantially in Period II and III. Reduction in the cost of debt should have induced companies to rely more on borrowings. On the contrary, despite the reduction in effective cost of debt, the proportion of borrowings in total liabilities has gone down. This reveals that companies avoided tax by debt financing when STR ruled high, and simultaneously with reduction in the STR over the years, debt has become somewhat unattractive as an instrument to shelter corporate income. This has been facilitated by policies favoring equity financing by companies. We now proceed to examine the extent of tax avoidance due to tax savings arising out of several tax reliefs and concessions, which can be estimated by first working out the difference between STR and ETR and then applying this on PBT. When the resultant values are expressed as percentage of PAT, they provide insights into extent of tax avoidance practices by resorting to several tax reliefs. That is, Tax savings from tax relief measures = ((STR − ETR) ∗ PBT)) / PAT 100

52

J. D. Rajakumar

Table 3.12 Trends in cost of borrowing (in %) Types of companies

Period I

Period II

Period III

Period I

Period II

Period III

Nominal cost of borrowing

Effective cost of borrowing

NGNF PLC

11.4

6.6

8.7

6.4

4.3

5.8

NGNF PTC

12.1

7.3

7.2

6.8

4.8

4.8

All companies

11.4

6.6

8.2

6.4

4.3

5.4

FDI companies

13.3

6.2

9.0

7.4

4.0

6.0

Note 1. NGFC PLC refers to non-government non-financial public limited companies 2. NGFC PTC refers to non-government non-financial private limited companies 3. All companies includes NGFC PLC and NGFC PTC 4. FDI companies refers to foreign direct investment companies Source Author’s calculations based on RBI’s studies of company finances

The tax savings from several tax relief measures stood very high as percentage of PAT in Period I and then declined substantially in Period II (Table 3.13). It may be recalled that corporate STR remained low in Period II compared to Period I. Although this has gone up in Period III, it is still far from what has been observed in Period I. This may be partly due to reduction in direct tax rates which would have increased the tax compliances of companies, tax rationalization pursued along with reduction in the STR, and also improved tax administration. These evidences basically indicate that corporates have reduced resorting to tax avoidance practices, particularly when STR has been considerably brought down. Table 3.13 Trends in tax savings arising from tax relief measures (as % of profit after tax)

Types of companies

Period I

Period II

Period III

NGNF PLC

19.6

12.0

10.4

NGNF PTC

12.4

0.5

−0.2

All companies

19.5

11.6

10.5

FDI companies

12.3

6.0

5.5

Note 1. NGFC PLC refers to non-government non-financial public limited companies 2. NGFC PTC refers to non-government non-financial private limited companies 3. All companies includes NGFC PLC and NGFC PTC 4. FDI companies refers to foreign direct investment companies Source Author’s calculations based on RBI’s studies of company finances

3 Corporate Response to Public Policy Changes: Some Intriguing Aspects

53

3.6 External Sector Orientation A major shift in the external sector related policies in the early 1990s was centered on export-led growth strategy. In the milieu of trade liberalization, corporates in India would have become more dependent on imports of technology, inputs and related services in order to stay competitive in the domestic market, even while producing for world market. In the ultimate analysis, the gain to the country, when viewed from balance of payment (BoP), is the net earnings in foreign exchange. While several studies have examined the export and import performance by products, this section makes an attempt to examine earnings and spending in foreign currencies of companies using RBI data. To begin with, we have examined earnings in foreign currencies, expressed as percentage to sales (Table 3.14). Consistent with the expected outcome of trade liberalization, earnings in foreign currencies by all categories of sample companies rose considerably from 13.1% of their sales in Period I to 23.6% in Period II. Though it declined to 21.5% in Period III, the level is far higher compared to Period I. Earnings in foreign currencies are more among NGNF PLC, compared to FDI companies. Most of these earnings have come by exports of goods and services. Export intensity, that is, exports as percentage of sales, stood at 10.4, 17.6 and 14.8% in Period I, II and III, respectively, in the case of entire set of sample companies. Compared to FDI companies NGNF PLC as a whole remained more export intensive in all the periods. It is possible that FDI companies tend to remain domestic market oriented, whereas non-FDI companies have increased their global market orientation (Rajakumar 2014a). The share of exports in total earnings in foreign currencies have, however, been dwindling; for instance, for all sample companies together, export as percentage of foreign earnings stood at 79.7% in Period I, which declined to 74.7% in Period II and further down to 68.8% in Period III. The same for FDI companies stood at 81.1, 69.6 and 51.7% in Period I, II and III, respectively, which suggests that exports contribution to earnings in foreign currencies in FDI companies have been shrinking over the years. Although the focus on export-led growth strategy has been given effect to by corporates with their increased earnings in foreign currencies, the reduction in the share of exports of merchandise goods is a pointer of increasing reliance on earnings through non-merchandise items. Similar trend has also been noticed in respect of expenditure in foreign currencies as percentage to sales. For all sample companies, this stood at 15.4% of their sales revenue in Period I with a whopping rise to 27.3% in Period II, though dropped to 23.8% in the subsequent period. The spending in foreign currencies remained more in NGNF PLC, very closely followed by FDI companies. Expenditure in foreign currencies comprises expenditure on account of imports of raw materials and components, stores and spares, and capital goods, and non-imports expenditures such as technical fees, royalties, dividends, interest, traveling expenses, professional and consultation fees, and so on.14 The import intensity, that is imports expenditure as percentage of 14

Remittances of technical fees and royalties are mostly for technical collaborations. Technical fees are lump sum payments, whereas royalties are recurring payments made for using unpatented

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Table 3.14 Earnings and expenditure in foreign currencies Types of companies

Period I

Period II

Period III

Earnings in foreign currencies as % of SALES

Period I

Period II

Period III

Exports as % of sales

NGNF PLC

13.1

24.0

24.5

10.4

17.9

17.1

NGNF PTC

13.4

16.8

12.7

9.8

13.2

7.2

All companies

13.1

23.6

21.5

10.4

17.6

14.8

FDI companies

13.2

19.4

21.9

10.7

13.5

11.3

Expenditure in Foreign currencies as % of sales NGNF PLC NGNF PTC

15.6

27.9

26.8

Imports as % of sales 12.9

22.8

20.9

8.5

17.6

13.0

7.1

15.2

8.6

All companies

15.4

27.3

23.8

12.8

22.4

18.1

FDI companies

13.8

25.4

25.5

11.0

19.5

17.5

NGNF PLC

Net earnings in foreign currencies as % of sales

Net earnings in foreign currencies as % of gross value added

−2.5

−3.9

−2.4

−10.6

−16.2

−11.2

4.9

−0.8

−0.3

22.2

−3.2

−2.3

All companies

−2.3

−3.7

−2.4

−9.8

−15.6

−11.3

FDI companies

−0.6

−5.9

−3.6

−2.4

−24.0

−16.2

NGNF PTC

Note 1. NGFC PLC refers to non-government non-financial public limited companies 2. NGFC PTC refers to non-government non-financial private limited companies 3. All companies includes NGFC PLC and NGFC PTC 4. FDI companies refers to foreign direct investment companies Source Author’s calculations based on RBI’s studies of company finances

sales, has been worked out to discern the dependence of corporates on the imported inputs as well as capital goods.15 On the whole, corporates’ reliance on imports, whether they are inputs or capital goods, has increased. Import used to be 12.8% of sales for the entire set of sample companies in Period I, which went up to 22.4% in Period II. It dropped to 18.1% in Period III. While all categories of companies know-how and services. Dividends are remitted for foreign equity participation. RBI discontinued publishing these information from 1993–94 in the case of public and private limited companies, and 2008–09 for FDI companies. It however clubs all such non-imports spending under an item ‘Other Expenditure in Foreign Currencies’. In RBI’s studies, imports are valued at cost, insurance and freight (cif), whereas exports in terms of freight on board (fob), which are consistent with the valuation of imports and exports in the country’s balance of payments. 15 In the literature, the following measures of import intensity have been used: Raw materials and components imported as percentage of Total raw material and components consumed; Stores and spares imported as percentage of Total stores and spares consumed; Raw material, components, stores and spares imported as percentage of Sales; Capital goods imported as percentage of Spending on purchases of capital goods; and Non-import spending as percentage of Sales. Invariably, the import intensity shows a rising trend. For further details, see Mani (1991), Sathe (1997) and Rajakumar (2014).

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displayed a similar pattern, the import dependence of NGNF PLC is very much on the higher side and also of FDI companies. Rajakumar (2014a) further observed a rising trend in the imported inputs as percentage of raw materials and stores and spares consumed as well as imports of capital goods as percentage of spending on capital goods. These pieces of evidence suggested a weakened emphasis on sourcing inputs indigenously and increased reliance on imported capital goods. Both are related because technology developed abroad may have reference to use of inputs available abroad; the suggestion here is that the technological capability of companies is yet to be harnessed. In fact, import expenditures as percentage of total expenditures in foreign currencies gradually declined for all sample companies, that is, from 82.9% in Period I to 82% in Period II and further to 76% in Period III. While this trend remained the same for all categories of companies, the falling share of import expenditures among FDI companies stands out. As noted above, non-import expenditures mostly pertain to technical collaborations and transfer of technology and capital. Thus, the increasing outflow on account of non-import expenditure is perhaps an indicator of how poorly the corporates have responded to the emerging competition by relying more on import of technology rather than indigenously developing them. Rising Dent Net Earnings in foreign currencies It may be recalled that one of the underlying forces for ushering in economic reforms was the balance of payment crisis, which rocked the economy in the early 1990s. Thus, the external sector related reform policies had aimed to surmount balance of payment problems; it also perforce implied that by facilitating the corporate engagement with the rest of the world, balance of payments situation would improve. In order to understand the outcome of corporates’ engagement with global economy, net earnings in foreign currencies have been analyzed. For this, total expenditures in foreign currencies including merchandise imports have been netted out from total earnings in foreign currencies including merchandise exports. Positive net earnings would mean inflow of foreign exchange is less than their outgo. As this covers trade and related services, it resembles current account balance of a country. We relate net earnings in foreign exchange to both sales and GVA, to represent them as percentage of the sector’s output and income, respectively (Table 3.14). First of all, there is deficit (−) in all categories of companies with their earnings in foreign currencies considerably falling short of their spending, except in NGNF PTC only in Period 1, that is, companies generally report deficit in their external sector related transactions. Secondly, the magnitude of deficit is higher in Period II when the country witnessed accelerated economic growth. To illustrate, net foreign exchange earnings of all sample companies was in the order of (−) 2.3% of sales and (−) 9.8% of GVA in Period I, (−) 3.7% of sales and (−) 15.6% of GVA in Period II, and (−) 2.4% of sales and (−) 11.13% of GVA in Period III. And, finally, FDI companies have higher order of deficit in Period II and III, than that of their counterparts. Since outgo imply transfer of resources, the large deficit experience of FDI companies when economic growth remained relatively higher in Period II and III imply transfer of benefits accruing from economic growth.

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3.7 Understanding the Economy and Corporate Sector in Its New Incarnation In the milieu of last two and a half decades, the role of private corporate sector in Indian economy has become enlarged. The PCS’ share in country’s NDP, capital formation and savings increased over the years. More importantly, PCS has become diversified and contributed to the broad basing of economic activities. As these trends mirror expected outcome of the policy changes, there has been appreciable response of PCS to policy reforms. In the latest NAS 2011–12 series, QCs have been included along with companies and cooperative societies under PCS. This has brought about major changes in the relative importance of the sector. The distribution of factor income of PCS shows certain interesting trend. The operating surplus, comprising property incomes and profit/loss, showed a substantial rise as percentage of country’s NDP as well as corporate NDP, with a simultaneous decrease in the share of compensation to employees. Operating surplus in the country’s NDP has also gone up, and this has largely been on account of the sector’s experience. Analysis based on data culled out from RBI’s studies of company finances revealed that the share of property incomes, particularly interest share, in companies NVA declined considerably with a concomitant increase in profit share. Analysis of financing pattern of companies brought out the increasing reliance on own resources (net worth or shareholders fund) with simultaneous decline in their reliance on borrowings. Keeping in line with policy changes in financial sector, corporates have an overwhelming thrust on equity financing as opposed to debt financing. Thus, the benefits of corporate growth have been distributed to shareholders of companies mediated by stock market. It is not surprising, however, because, as brought out by the trend in Tobin’s Q, market value of companies fuelled corporate investment activities. Two major issues can be highlighted here. One, market valuation matters for corporate investment and hence for the pace of investment activities in the economy; this makes the economy instable because economic growth is now inevitably tied to speculative activities in the capital market. And, two, with skewed shareholding pattern, benefits of economic growth are likely to be unevenly distributed, thus, contributing to rising income inequality in the society. With reduction in the direct tax rates of companies, corporates’ tax incidence has gone up with simultaneous reduction in tax avoidance. This would help to augment resources of the states, but if this could go a long way in helping to reduce income inequality remains a moot question. Furthermore, with net earnings in foreign currencies remaining deficit, the sector cannot be said to have helped strengthening balance of payments; rather they may likely to precipitate any pressure on local currencies. Thus, the focus on enlarging the role of corporates during the last two and a half decades has made the economy vulnerable to uneven distribution of income, unstable investment activities as market valuation drive corporate investment decisions, and deepening of balance of payment problems. Though corporate response has been in line with expected outcomes, the implication is that they have sown seeds for deepening income inequality and making

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the economy more vulnerable to decisions under the dictates of market forces. Market incentives are fundamentally different, and once economy comes under their spell, the safeguards available for maintaining the tempo of effective demand in the system would wither away, which is likely to cause instability in the growth process.

References Central Statistical Organisation (2007) National accounts statistics sources and methods 2007. Ministry of Statistics and Programme Implementation, New Delhi Central Statistical Organisation (2012) National accounts statistics sources and methods 2012. New Delhi Fama EF, Miller MH (1972) The theory of finance. Dryden Press Government of India (1992) Tax reforms committee final part: part I (Chairman: Raja J Chelliah). Ministry of Finance, New Delhi Mani S (1991) Export liberalisation and import dependence. Econ Pol Weekly 26(27–28):1693– 1696 Mintz J (1996) Corporation tax: a survey. Fisc Stud 16(4):23–68 Nayyar D (2015) Birth, life and death of development finance institutions in India. Econ Pol Weekly 50(33):51–60 Patil RH (1979) Tax treatment of interest costs in the context of increasing reliance on debt financing. Econ Pol Weekly 14(38):1613–1621 Rajakumar JD (2005) Corporate financing and investment behaviour in India. Econ Pol Weekly 40(38):4159–4165 Rajakumar JD (2009) Corporate financing and tax environment in India. IUP J Public Fin 7(2&3):25–42 Rajakumar JD (2011) Size and growth of private of corporate sector in Indian manufacturing. Econ Pol Weekly 46(18):95–101 Rajakumar JD (2014a) Foreign exchange spending and earning of corporates in India. Econ Pol Weekly 49(45):75–78 Rajakumar JD (2014b) Corporate financing pattern in India: changing composition and its implications. IUP J Appl Financ 20(4):5–21 Rajakumar JD (2014c) Corporate response to direct tax reforms. Econ Pol Weekly 49(51):67–70 Rajakumar JD (2014d) Trends in corporate profitability. Econ Pol Weekly 49(36):75–78 Reddy YV (1999) Financial sector reform: Review and Prospects. Reserve Bank of India Bulletin 53(1):33–93 Sathe D (1997) Import intensity of India’s exports some fresh evidence. Econ Pol Weekly 32(80):M31–M44

Chapter 4

Ownership Control and Board Governance of Indian Business Groups: Continuity or Change? Jayati Sarkar

Abstract This chapter analyzes how the ownership, control, and board governance of Indian business groups have evolved over time against the backdrop of evolving laws and regulations in India. The analysis is based on a panel data of group affiliated and unaffiliated firms for the period 2005–2018 during which the governance reforms that were initiated in the earlier years took root, and several new ones were introduced through revisions of existing regulations and laws. The chapter seeks to answer mainly two questions. First, have the nature of the agency problems pertinent to business groups as manifested in their ownership and control structures fundamentally changed in response to dynamic changes in their institutional environment? Second, have reforms introduced to change the ways in which groups are governed by the board of directors made any impact on the way these groups are actually governed? Contrary to the expectations drawn from the institutionalist perspective that the relevance of business groups that fill institutional voids will wane as markets develop, the analysis in this chapter points to the continued predominance and persistence of Indian business groups within the corporate sector. Several of the groups, such as the Tatas and Birlas, which were established in the pre-independence era, have continued to remain in leadership positions with a handful of large business groups continuing to dominate the sector, irrespective of the changes in the institutional environment. Big groups have become even bigger in terms of their asset base, and changes in the relative positions of groups at the top end of the distribution have been sticky at best even after more than hundred years of their existence and continued entry of new groups from time to time. Within groups, ownership structures have become more concentrated over time, with promoters of almost all groups now having majority control in all the listed firms of the groups. The pervasiveness, persistence, and dominance of promoters in Indian business imply that there is little scope for monitoring internal management by other large block holders.

J. Sarkar (B) Indira Gandhi Institute of Development Research, Mumbai, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_4

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4.1 Introduction Business groups in India have continued to remain a dominant organizational form despite structural shifts in the policy and institutional environment over different time periods. In the post-independence era, one of the most critical shifts in this respect has been the change in the corporate governance framework of firms introduced through far reaching governance regulations since the early nineties, and through the enactment of a revised legislative framework under the Companies Act, 2013. The objectives of corporate governance reforms in India, as in many emerging economies with business group dominance, have been to reduce agency costs manifested in minority shareholder expropriation by controlling shareholders, and to improve firm performance. Thus, reforms have focused on bringing about greater transparency in the ownership and control structure of firms, reducing insider control of the board of directors by increasing board independence, and improving disclosure requirements pertaining to related party transactions and financial statements. Much of such reforms have automatically brought under its purview firms affiliated to business groups by virtue of their complex ownership and control structure as manifested in equity pyramids, cross-holdings and opacity in equity linkages, family dominance of board of directors, prevalence of related party transactions, and presence of internal capital markets. As the existing body of empirical research has shown, such characteristics have had implications for incentives of controlling insiders of business groups to expropriate outside minority shareholders with consequent impact on the value of group affiliated firms. In view of the above, the objective of this chapter is two-fold. First, it seeks to examine the evolution of the governance structure of firms affiliated to business groups with respect to two key characteristics of business groups, namely, ownership and control, and composition of the board of directors. Second, keeping the objectives of governance reforms in the background, and using a panel of group affiliated firms in India for the period 2005–2018 as well as of the top Indian business groups, the chapter offers a big picture of how the governance of group affiliated firms has evolved over time in relation to its intended objectives. In doing so, the paper evaluates whether de jure corporate governance reforms largely intended for business groups have translated to de facto changes in their governance structure or whether there has been overall persistence in these two key characteristics despite such reforms. The empirical analysis in this chapter is based on two types of samples, each of which covers the financial years from 2005 (April 1, 2004 to March 31, 2005) to 2018 (April 1, 2017 to March 31, 2018). The first sample consists of all firms, listed and unlisted, those are reported in the Prowess database. We use this sample to put into perspective the relative dominance of business groups in the Indian corporate sector. Using data for the year 2018, we identify 569 business groups in this sample each of which satisfies two criteria namely that the group has at least two firms, listed or unlisted, and has non-missing values for total assets. The second sample consists of only listed firms belonging to these 569 business groups. We use this sample to trace the evolution of ownership structures and board composition since

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the slew of corporate governance reforms in the last three decades, as well as the discussion in the literature, are directed mostly to listed firms. This sample consists of an unbalanced panel of 3,065 firm-year observations, with the number of firms varying from 388 in the year 2005 to 581 in the year 2018. The rest of the chapter is organized as follows. With Sect. 4.1 being the introduction, Sect. 4.2 examines the origins and early development of business groups in India and discusses their fundamental organizational elements. The incidence, characteristics, and dynamics of the evolution of business groups against the backdrop of institutional changes are analyzed in Sect. 4.3. Section 4.4 examines in detail the ownership and control structures of business groups, how these have evolved over time, and the implications of such structures for corporate governance. Section 4.5 examines the role of the board of directors in mitigating governance problems in Indian business groups in light of the various changes in the regulatory and legislative framework during the period of the study. Concluding comments are made in Sect. 4.6.

4.2 Business Group as an Organizational Form A business group, as defined in the Indian context, can be considered as an agglomeration of both privately held and publicly traded firms operating in different lines of businesses, each incorporated as a legal entity, but where all the firms are bound together usually under the common ownership and control of a family.1 This definition largely draws from the characterization of Hazari (1966: 4) who defines a group as “consisting of units which are subject to the decision-making power of a common authority” and functions as a single organization although each of the corporate units under its control has a separate legal entity. The definition is also at par with how Indian groups were defined under the Monopolies and Restrictive Trade Practices (MRTP) Act of 1969 that dealt with the concentration of economic power among Indian business groups, whereby a group was considered to constitute of (i) “two or more individuals, association of individuals firms, trusts, trustees or bodies corporate (excluding financial institutions), or any combination thereof, which exercises or is established to be in a position to exercise, control, directly or indirectly, over any body corporate, firm or trust, and (ii) associated persons” (MRTP 1969: 6).2 In all these definitions, the key element is the control exercised on firms by an apex body (i.e., the family) through equity channels (equity ownership) as well as non-equity channels (administrative control through board of directors, inter-locking directorships, related party transactions).

1

This definition broadly conforms to the one used by Khanna and Palepu (2000) but brings into its ambit privately owned and controlled firms under a group’s control. 2 https://www.mca.gov.in/Ministry/actsbills/pdf/The_Monopolies_and_Restrictive_Trade_Practi ces_Act_1969.pdf.

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On the basis of several well-cited historical accounts on Indian business,3 one can trace the beginnings of family-owned business groups in industrial activity to the second half of the nineteenth century. Prior to this period, industrial activity was monopolized by European business houses, and the participation of Indians in business activities was confined essentially to trading and money lending enterprises delineated by family, caste, and ethnicity. The beginnings of the first business group in India in the pre-independence era, the Tata Group, can be traced back to the setting up of the Bombay Spinning and Weaving Company in July 1854 by Cowasji Nanabhai Davar that was followed by the entry of a large number of textile mills promoted by other entrepreneurs. Few years later, the foundations of other major business groups such as the Khataus, Birlas, and the Mafatlals were laid. The motivation of Indian business leaders to float new ventures, to expand and diversify, coupled with the need for capital to fund such diversification owing to an underdeveloped stock market and banking system led to the evolution of the business group structure over time. Most industrial ventures during this time were floated and financed by families engaged in trade and commerce, with the first round of industrial projects setting off a chain reaction where surplus funds generated in these projects were re-invested to promote other industrial and finance activities. This led to the incorporation of many of the business ventures as joint stock companies, where family members and acquaintances were issued shares to retain family control. It also set off a process of vertical and horizontal integration that bypassed the hazards of market transactions, generated scale, and scope economies, and led to the formation of business group as an institution in India (Mehta 1955). Finally, a business group typically had a managing agency which enabled the group to cope with a deficient managerial market in the early years of industrialization, as also ensured family control over group affiliates. As Tripathi (2004) notes, during 1918–39, the share of Indian business groups in capital employed more than doubled from 13 to 34%. Further, three of the top four business groups were controlled by Indians (Hazari 1966). Post-independence, two structural breaks in the institutional environment impacted the evolution of groups. First, the post-independence years up to 1991 of extensive regulation of business groups by the government, and second, the post1991 period of liberalization and globalization of the Indian economy when structural reforms were initiated in 1991. Despite the curbs on the scale and scope of private sector activity placed by the industrial licensing policy till the mid-eighties, and the restrictions placed on the expansion of asset base of big businesses through the MRTP Act of 1969, business groups continued to find their footing well into the 1960s and 1970s. The structural reforms since the early nineties saw the abolition of licensing and the withdrawal of the MRTP Act, and as a consequence, large business houses

3

For comprehensive historical accounts of Indian business groups, see among others, Tripathi (2004), Piramal and Herdeck (1986), Mehta (1955), Dutta (1997) cited in Sarkar (2010). The account on the evolution of Indian business groups in this section draws significantly from Sarkar (2010).

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were free to invest, expand and diversify consistent with their capabilities. Concomitantly, financial sector reforms led to the deregulation of the equity markets as well as that of the banking sector to ease the bottlenecks in external finance and allow for a greater play of market forces in determining the availability and allocation of finance for corporate sector investment. Thus, while prior to the financial sector liberalization, on account of the dormant and underdeveloped capital market, internal financing was dominant as the source of finance for Indian corporates, post liberalization, the importance of external finance in the form of bank borrowings and raising capital from the equity markets have on an average been higher (Sarkar and Sarkar 2012; Rajakumar 2014). Finally, the corporate governance reforms that were initiated since the late nineties changed the institutional environment in which business groups, and corporates at large have functioned. While economic liberalization ensured that business decisions are market based rather than taken by government fiat, and relaxed the constraints on external finance for firms, corporate governance reforms were initiated in the late nineties to put mechanisms in place to enable effective monitoring of firms by the suppliers of finance. Comprehensive reforms in this area sought to strengthen effective protection of shareholders through promoting higher standards of information disclosure and enforcement, and company board structure and procedures were reformed to make the board of directors and management more accountable to the shareholders. How have Indian business groups as an organizational form responded to the structural changes in their institutional environment? The dynamics of the evolution of business groups in India in the context of an evolving institutional environment can be understood from an institutionalist perspective which sees a business group as a diversified hybrid organizational structure that typically comes up in response to missing markets and weak institutions, combining the functions of both firms and markets (Khanna and Yafei 2007; Leff 1976). In developing economies like India, weak financial markets with imperfect information, imperfections in the managerial markets, weak investor protection, and inadequate rule of law have been cited as some of the shortcomings of the institutional environment, which may have given rise to business groups that can produce these public goods for the benefit of their affiliates (Khanna and Yafei 2007). As a corollary of this hypothesis, as markets emerge and institutions are strengthened, the comparative advantage of the group structure as quasi-market institutions can be expected to diminish vis-à-vis unaffiliated firms. While the institutionalist perspective predicts the diminishing role of business groups as markets develop and institutions strengthen, alternative perspectives point to the continued dominance of the group structure notwithstanding institutional development. For instance, as Sarkar (2010) notes, the sociological perspective views business groups as social networks of firms bound by formal and informal ties, with the “axes of solidarity” among group affiliates identifiable along geographical, political, ethnic, kinship and religious lines (Granovetter 1995). Given that Indian business groups are deeply rooted in the joint family structure and are not merely economic structures but a source of “social identity” bound by relational contracts and interlocked directorships within the community with high degrees of trust and reciprocity (Dutta 1997; Encarnation 1990), it is unlikely that business groups, once

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acquiring a predominance as an organizational form, will lose its comparative advantage as markets develop. There could be non-diversification related benefits too that stem independent of market imperfections. For example, Ramaswamy et al. (2012), using longitudinal data on group affiliated firms, find that affiliation to groups has brought in performance benefits to firms even when markets have developed, thereby concluding that a group structure can generate non-diversification related benefits contrary to what is hypothesized under the institutionalist perspective. On the other hand, Kali and Sarkar (2011), using a case study of Indian firms, find that group affiliate firms are often engaged in activities away from the business of the core firm of the group, which they think are suggestive of the fact that these firms act as destination points for tunneling resources from the top to the bottom of the ownership pyramid for benefitting the family at the expense of the minority shareholders.

4.3 Characteristics of Indian Business Groups This section presents an evaluation of the importance of Indian business groups in corporate sector activity as of 2018, as well as examines some dynamics of the evolution of major business groups at different time points since 1980 and up to 2018. The data used for these exercises have been sourced partly from previously published accounts of Indian business groups and partly from the Prowess database, a computerized database containing detailed time series information (from 1990 onwards) published in annual reports, along with stock market data, ownership information, and corporate governance characteristics on many companies.

4.3.1 Incidence of Business Groups Annexure 4.1 at the end of this chapter presents key aspects of the Prowess database from which the data on Indian business groups and firms affiliated to business groups have been culled. An understanding of this data as presented in Table A.1 is important to get an estimate of the importance of business groups in India, and the extent to which information is available in the public domain on these groups. Depending on the analysis at hand, different samples are drawn from the set of groups reported in the Prowess database as of November 2018. As can be seen from Table A.1, 734 distinct Indian business groups are identified and reported in the Prowess database. By distinct, one means that each group is identified by a unique name, and distinct firms are listed under each group reported. With regard to these 734 groups, as of 2018, the total number of firms, those that are listed on either the National Stock Exchange or the Bombay Stock Exchange or both, and also those that are unlisted is 11802. Several of the 734 groups have only one firm reported per group. Given that a group makes sense only if has at least 2 firms, using this filter brings down the number of groups reported to 702 comprising 11,771 listed and unlisted firms.

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However, this filter also includes groups with no total assets on account of the fact that Prowess does not report any asset figures for any of the group affiliated firms. Thus, the final filter that is used to generate the groups with non-zero total assets yields 569 groups. A comparable estimate of the number of groups in 2006 was 560 (Sarkar 2010). Similar to Panel A in Table A.1, Panels B, C, D, and E provide information on business groups with at least one listed firm, with at least one unlisted firm, groups with only listed firms, and groups with only unlisted firms, respectively. Judging from the estimates provided under all the panels, one can conclude that a large majority of Indian business groups have a combination of both listed and unlisted firms. Table 4.1 presents the summary statistics of some basic characteristics of the 569 Indian groups with non-zero assets, namely the average asset size of groups, the average asset size of groups after considering the assets of only listed firms in any group, percentage share of assets of listed firms to total assets of a group averaged across all groups and the percentage share of listed firms in total firms in a group, averaged across all groups. As is evident from the estimates presented in the Table, while, on an average, around 51% of group firms are listed, these firms account for around 72% of group assets, and in some cases around 100% of group assets (in case of groups in Panel D of Table A.1).

4.3.2 Dominance of Business Groups A large number of business groups in India have persistently dominated private corporate sector activity despite structural changes in its institutional and governance environment from time to time. Figure 4.1 presents the share of group affiliated firms in total corporate sector assets held by privately owned Indian firms which comprise group affiliated firms and non-affiliated or standalone firms. The estimates are presented for the share of group affiliated firms among the top 50 firms, top 100 firms, top 500 firms, and for all firms taken together, at three points in time, 1991, 2001, and 2018. As can be seen from the figure, the presence of group affiliated firms among the top 50 private sector firms has been more than 80% at all the three time points, and 27 years apart, between 1991 and 2018.4 Estimates published for years in-between (2001 and 2006) also corroborate this finding. What is striking is that the share of group affiliated firms in the top 50 firms in 2018 is the highest, at around 91%. The picture is very similar for the top 100 and top 500 firms wherein the share of group affiliates is not only consistently higher than 80%, but also registers an increase for 2018. However, the share of group affiliates in all firms is lower at around 73% in 2018 and has steadily gone down across the three years suggesting that the presence of standalones among the smaller sized firms has increased over time.

4

Comparable estimates for 1996 and 2006 are presented in Sarkar (2010).

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Table 4.1 Characteristics of group affiliated and standalone firms: 2018 Group affiliates

Standalones

All firms

A. Listed + Unlisted Total assets (Rs. Million)

127,285,657.40

4,61,77,261.90

17,34,62,919.30

Total number of firms

5086

11,232

16,318

Share in total assets

73.38

26.62

100

Share in total number of firms

31.17

68.83

100

Mean asset size (Rs. Million)

25,026.67

4,111.22

10,630.16

Median asset size (Rs. Million)

1033.85

424.45

532.40

B. Listed firms Total assets (Rs. million)

9,15,61,979.50

2,22,28,604.70

112,690,584.20

Total number of firms

1268

3311

4579

Share in total assets

81.25

19.75

100

Share in total number of firms

27.69

72.31

100

Mean asset size (Rs. Million)

72,209.76

6381.34

24,610.30

Median asset size (Rs. Million)

4982.35

397.20

670.00

3,57,23,677.9

25,048,657.2

60,772,335.10

C. Unlisted firms Total assets (Rs. Million) Total number of firms

3818

7921

11,739

Share in total assets

58.79

41.21

100

Share in total number of firms

32.52

67.48

100

Mean asset size (Rs. Million)

9356.65

3162.31

5176.96

Median asset size (Rs. Million)

528.05

441.70

472.60

Source Author’s computation based on the Prowess database 100.00 90.00

88.00

91.30 82.92

86.07 84.72

89.88 82.70 81.12

86.46

80.00

82.02

77.75

73.38

70.00 60.00

50.00 40.00 30.00 20.00 10.00 0.00 Top 50

Top 100 1991

Top 500 2001

Top All

2018

Fig. 4.1 Share of group affiliated firms in total assets: 1991–2018. Source Author’s computation from the Prowess database

4 Ownership Control and Board Governance of Indian Business Groups …

67

180000 160000 140000 120000 100000 80000 60000

40000 20000 0 Reliance Tata (177) [MA] (72)

Bharti Vedanta Adani Birla Reliance Larsen & OP (111) Aditya [A A] Toubro Jindal Telecom (22) (18) (130) (80) (103) (60)

Median Assets (Rs. Million)

Bajaj (29)

Mean Assets (Rs. Million)

Fig. 4.2 Mean and median assets: Top 10 Business Groups Notes 1. Figures in brackets are the number of firms in each group with positive assets. 2. Reliance [MA] is Reliance Mukesh Ambani 3. Reliance [AA] is Reliance Anil Ambani. Source Author’s computation from Prowess database

The dominance in group affiliates in the private sector can be clearly understood from estimates of mean and median asset size of group affiliated and standalone firms. These estimates and related statistics are presented in Table 4.1. First, consistent with Fig. 4.1, the share of group affiliates in total assets across such affiliates and standalones is around 73%, and as can be seen from the Table, group affiliates account for only 31% of the total firms. In contrast, a disproportionate percentage of standalone firms, 68.8, account for about a quarter of total assets (26.6). This picture is even more skewed for listed firms (Panel B of Table 4.1). Second, estimates of average asset size of group affiliates and standalones, both for all firms and for listed firms show that the asset base of group affiliates is higher than that of standalones by several multiples; six times larger when all firms are taken together and 11 times larger when considering listed firms. The difference is relatively less in the case of unlisted firms, although in this category, affiliates are still three times larger than that of standalones. Third, it is important to see the stark difference between the mean and median estimates of size especially for group affiliate firms; in Panel A, estimates show that while the average asset size of group affiliates is about |25,026 million, the median asset size is |1033 million, which suggests that there are a few disproportionately large firms among the group affiliates which have driven up the average size (Fig. 4.2). Table 4.2 lists the top ten business groups in India as of 2018, along with the year of foundation, total assets, and major lines of business.5 As one can see from the Table, each group is well diversified. Further, except for the Adani Group, listed firms account for more than 50% of total group assets. Finally, except for one of the 5

See Sarkar (2010) for a comparable list for the year 2006.

68

J. Sarkar

groups (Larsen and Toubro), all other groups among the top 10 are family-controlled business groups. A key feature of business group presence in India is that since independence, while the number of distinct groups at any point of time has run into the hundreds, with 569 such groups identified as of 2018, only a few of these groups have accounted for a disproportionate proportion of total business group assets. In other words, much of the business group activity in India is driven by a few large groups, as is the case especially in many emerging economies where such groups dominate, be it Brazil, South Korea, Mexico, or Chile, but the uniqueness of India lies in the fact that there is a long string of much smaller business groups leading to striking level of inter-group inequality. Figure 4.3 presents the Lorenz curve for business group assets, capturing the relationship between the cumulative percentage of the number of groups with the cumulative percentage of the value of assets held by groups. What is striking from the Figure, is that in the year 2018, the top 10% of business groups collectively held almost 80% of the total assets of all business groups put together, while the bottom 10 groups accounted for mere 10% of the total. If we go by concentration ratios as the measure of dominance of business groups in India, estimates as of 2018 reveal that the 3-group concentration ratio among the top twenty business groups was about 41%. That group concentration has persisted over time and across institutional environments is evident from comparable estimates for earlier years (Sarkar 2010).

4.3.3 Persistence of Business Groups Two observations can be made from the analyses in Sects. 4.3.1 and 4.3.2. First, is the persistent dominance of business groups in terms of the share of total private corporate sector assets, and second, the predominance of a few large business groups among all groups. An additional aspect of the persistence with respect to the evolution of groups can be found in terms of whether there has been churning in ranking among the business groups, especially at the top end. As Sarkar (2010) and Khanna and Palepu (2005) argue, a persistence of the ranking among the top groups over extended periods of time in an emerging economy will signify a kind of path dependence in the evolution of groups; groups that were at an advantage in the early years of their incorporation, and filled up institutional voids when markets and institutions were weak, continue to adapt and thrive even when markets come up to fill up these voids. On the other hand, if there is a churning in the ranks across the groups with institutional change, that would imply differences across business groups in terms of their entrepreneurial responses and abilities to exploit/adjust to emerging market opportunities. Analysis by Khanna and Palepu (2005), tracking changes in relative ranking of the top fifty business groups over two thirty-year periods, 1939–69 and 1969–99, find that while there has been significant persistence of concentrated family ownership, the identities of the top business groups over time exhibited noticeable changes. Using narrower windows of ten years to coincide with structural shifts in the policy environments, Sarkar (2010) finds that between 1969 and 2006, while

Aditya Birla Group

Anil Dhirubhai Ambani (ADA) Group

Larsen and Toubro Group

Om Prakash Jindal Group

Bharti Telecom Group

3

4

5

6

7

1986

1952

1946

1966

1918

18 (4)

103 (11)

80 (4)

130 (9)

60 (8)

177 (31)

1875

Tata Group

2

(4) 72 (6)

(3)

(2)

Reliance Group [Mukesh 1966 Ambani]

1

Number of firms1

(1)

Founding year

Group name

Rank

Table 4.2 Top ten business groups in India—2018

2,975,089.70 (85.04)

2,982,927.30 (74.42)

3,228,669.90 (42.10)

3,743,489.00 (54.80)

4,214,454.00 (76.50)

8,436,188.50 (54.50)

11,235,210.90 (55.90)

(5)

Total assets (Rs. Million)

Sunil B. Mittal Family

Om Prakash Jindal Family

Non-family

Anil Ambani Family

Kumaramangalam Birla Family

Ratan Tata Family

Mukesh Ambani Family

(6)

Ownership

(continued)

8; Telecom, agri business, insurance, and retail

25; Hot rolled coils and other flat rolled products; power generation

20; Engineering and construction projects, heavy engineering and electrical and electronics, information technology

27; Communications, financial services, generation, transmission and distribution of power, infrastructure and entertainment

20; Aluminum and copper production, carbon black, cement, viscose staple fiber, insulators

33; Information systems and communications, engineering, materials, services, energy, consumer products and chemicals

20; Exploration and production of oil and gas, petroleum refining and marketing, petrochemicals, textiles and retail

(7)

Number of distinct 2-digit level NIC codes; Major Business Lines

4 Ownership Control and Board Governance of Indian Business Groups … 69

1993

Adani Group

Bajaj Group

9

10

29 (12)

111 (6)

22 (5)

Number of firms1

1,895,540.50 (81.33)

2,550,869.20 (38.50)

2,570,391.00 (82.50)

Total assets (Rs. Million)

Bajaj Family

Gautam Adani Family

Anil Agarwal Family

Ownership

13; Asset financing services, Motorcycles, Coal-based thermal electricity, Sugar, Securities investment services, Securities investment services, Finished Steel (Non-Alloy Steel)

18; Ports, Coal-based thermal electricity, Fund based financial services, Wholesale trade in coal,lignite and peat, Wholesale trade in vegetable oils

11; Metals and mining

Number of distinct 2-digit level NIC codes; Major Business Lines

Notes 1. 1 : Number of listed and unlisted firms under a given business group for which assets are reported in Prowess. 2. Figures in brackets in column 4 are number of listed firms in the group. 3. Figures in brackets in column 5 are the percentage of assets of listed firms in total assets of a business group Source Author’s computation based on the Prowess database

1934

1975

Vedanta Resources Group

8

Founding year

Group name

Rank

Table 4.2 (continued)

70 J. Sarkar

4 Ownership Control and Board Governance of Indian Business Groups …

71

Cumulative percentage of group assets

100 90 80 70 60 50 40

Lorenz Curve

30 20 10 0 0

20

40

60

80

100

Cumulative percentage of number of business Fig. 4.3 Lorenz curve of business group assets: 2018. Source Author’s computation from the Prowess database

there have been some changes in relative ranking, some groups going up the ranks, while some others going down, there have seldom been dramatic changes in relative positions, of moving more than five places up or down. To find out the relative rankings of groups in a period when substantive governance reforms were brought about in the form of more regulatory oversight on business groups that could impact their growth prospects, a period which also includes the continuing strengthening of markets, the analysis of Sarkar (2010) is extended from its last time point, 2006 to twelve years later, to 2018. The results of the analysis are presented in Table 4.3. Focusing on the period between 2006 and 2018, during those twelve years, eight new groups entered the top 20 whereas 12 groups continued to be in the list. Of these 20 groups, 5 groups had no change in ranks, and of all the rank changes that happened, either up or down, except for one group (Essar Ruia), none of the changes were more than five places. Of those business groups which were in the top 20 list in 1980, five continued to be in the list almost thirty years later, and there has been little churning in the top four spots of the ranking since 1990. The persistence of business groups in terms of their share in total corporate sector assets, the continued dominance of a few business groups over time both in terms of their share in total business group assets and the stickiness in terms of their relative ranking, along with the existence of 500 odd groups, implies that the group structure continues to be an optimal choice for organizing business in India. This could be a purely sociological phenomenon, given that groups have emerged historically as essentially family-based structures, or could also reflect expropriation motives, or, as Masulis et al. (2011) suggest, because of the extensive financing advantages of internal capital markets that provide a competitive edge to group firms vis-à-vis

Kirloskar

Hindustan Lever$

Larsen and Toubro$

13

Shriram

10

11

Bangur

9

12

Sarabhai

ACC

ICI

6

7

Thapar

5

8

JK Singhania

4

216.03

219.30

220.37

241.00

264.33

274.51

317.94

343.01

348.06

412.00

427.54

1431.99

Birla

Mafatlal

2

3

1538.97

Tata

Bangur

UB

Shriram

TVS

M A Chidambaram

Modi

Bajaj

Mafatlal

Thapar

J K Singhania

Reliance

Birla

Tata

1990

Group

Assets (in Rs.Mn)

1980

Group

1

Rank

674

716

800

909

1032

1192

1228

1297

1763

1829

3241

7235

7546

Assets (in Rs Mn)

Birla K. K

Jaiprakash

Sterlite Industries

Mahindra and Mahindra

Thapar

Bajaj

RPG Enterprises

Om Prakash Jindal

Larsen and Toubro$

Birla (Aditya)

Essar Ruia

Tata

Reliance

Group

2000

Table 4.3 Evolution of top twenty business groups: 1980–2018

6606.15

6649.65

7055.17

7222.19

7635.50

10,947.07

12,906.22

17,102.82

19,395.65

19,409.55

23,384.37

58,987.05

65,914.12

Assets (in Rs Mn)

2006

97,969.39

108,510.95

Assets (in Rs Mn)

26,040.34

35,538.01

45,513.94

Krishna

TVS

Bajaj

Mahindra and Mahindra

Larsen and Toubro$

Sterlite Industries4

12,849.59

13,737.13

14,805.32

14,998.47

17,891.05

19,239.43

Bharti Telecom 21,334.34

Om Prakash Jindal

Essar Ruia

Birla (Aditya)

Reliance (Anil) 46,666.86

Tata

Reliance (Mukesh)

Group

2018

4,214,454.00

8,436,188.50

11,235,210.90

Assets (in Rs Mn)

2,982,927.30

3,228,669.90

Essar (Ruia)

Mahindra and Mahindra

IndiaBulls

Bajaj

Adani

Vedanta Resources

(continued)

1,781,507.00

1,794,006.10

1,819,991.50

1,895,540.50

2,550,869.20

2,570,391.00

Bharti Telecom 2,975,089.70

Om Prakash Jindal

Larsen and Toubro

Reliance [Anil] 3,743,489.00

Birla Aditya

Tata

Reliance [Mukesh]

Group

72 J. Sarkar

156.29

150.36

ITC$

Walchand

19

179.26

166.33

Bajaj

186.03

Reliance

Mahindra and Mahindra

16

188.64

17

TVS

15

198.82

18

Modi

Top 20 (1990–2000)

14 5

Top 20 (1980–1990)

No Rank change

No Rank change

Number Continuing in

Number Continuing in

Entrants1

Murgappa Chettiar

Zee Telefilms

Lalbhai

Birla B. K

Krishna

M. A. Chidambaram

TVS

Entrants1 6

2000 Group

Number of New

437

479

537

570

620

626

633

Assets (in Rs Mn)

Number of New

Essar Ruia

Lalbhai

Nanda (Escorts)

Goenka

Mahindra and Mahindra

Walchand

Kirloskar

1990

Group

Assets (in Rs.Mn)

1980

Group

14

Rank

Table 4.3 (continued)

0

9

11

4220.50

4256.86

4804.35

5281.42

6173.44

6409.52

6588.20

Assets (in Rs Mn)

2006

No Rank change

Top 20 (2000–2006)

Number Continuing in

Entrants1

Number of New

Thapar

Birla K. K

I L and F S Group

Wipro

Videocon

RPG Enterprises

Jaiprakash

Group

5

16

4

7901.48

8934.86

9040.50

9120.87

10,293.36

10,707.58

12,067.57

Assets (in Rs Mn)

2018

No Rank change

Top 20 (2006–2018)

Number Continuing in

Entrants1

Number of New

Jaypee Group

DLF Group

Wadhawan (Rajesh K)

GMR

I L and F S

IDFC

Shriram Transport

Group

5

12

8

(continued)

1,091,126.40

1,134,319.90

1,166,944.10

1,176,292.50

1,473,085.90

1,483,575.20

1,521,350.10

Assets (in Rs Mn)

4 Ownership Control and Board Governance of Indian Business Groups … 73

Assets (in Rs Mn) 5 4 2 1 1 0

1990

Group

Number: Rank Up

Number: Rank Down

No. Rank Up2 : 5–10

No. Rank Up3 : > 10

No. Rank Down 5–10

No. Rank Down: > 10

Assets (in Rs.Mn)

1980

Group

2000

1

1

1

5

4

Assets (in Rs Mn)

No. Rank Down: > 10 0

No. Rank Down 5–10

No. Rank Up3 : > 10

No. Rank Up2 : 5–10

Number: Rank Down

Number: Rank Up

Group

2006

No. Rank Down: > 10

No. Rank Down 5–10

No. Rank Up3 : > 10

No. Rank Up2 : 5–10

Number: Rank Down

Number: Rank Up

Group

1

1

0

1

6

4

Assets (in Rs Mn)

2018

No. Rank Down: > 10

No. Rank Down 5–10

No. Rank Up3 : > 10

No. Rank Up2 : 5–10

Number: Rank Down

Number: Rank Up

Group

0

1

0

0

3

4

Assets (in Rs Mn)

Notes 1 refers to the number of groups that entered the Top 20 list in a given time/window and have not appeared in the previous windows. 2 refers to the number of groups whose respective ranks have moved up by five to ten places. 3 refers to the number of groups whose respective ranks have increased by more than ten places. Rank down is analogously defined. 4 Sterlite Industries was renamed Vedanta Resources in 2015 Sources Data for 1980 and 1990 sourced from Piramal (2003); data for 2000, 2006 and 2018 sourced from the Prowess database

Rank

Table 4.3 (continued)

74 J. Sarkar

4 Ownership Control and Board Governance of Indian Business Groups …

75

other firms that must rely predominantly on external sources of capital for their investments.

4.4 The Nature of the Governance Problem of Indian Business Groups A survey of the academic and policy literature on corporate governance reveals multiple definitions of the concept of governance of corporates. These range from the agency perspective of minimizing the cost in aligning managers and shareholder’s incentives to mitigate self-interested managerial behavior (Jensen and Meckling 1976), to the corporate finance perspective of designing economic and legal mechanisms that ensure that suppliers of finance get a return on their investment (Shleifer and Vishny 1997), to the all-encompassing definition of corporate governance dealing with conducting the affairs of a company that is fair to all stakeholders, and to ensure ethical conduct, openness, integrity and accountability of business (SEBI 2003).

4.4.1 Agency Problems in Business Groups Notwithstanding a plethora of definitions and theoretical perspective on corporate governance, the dominant theoretical paradigm in economics and finance is the agency and corporate finance perspective that focuses on agency costs between outside shareholders and inside management whereby on account of asymmetric information between shareholders and managers, or unobservable efforts of the managers (moral hazard), managers are able to take self-serving actions that are against the interests of the shareholders. As has been widely discussed in the governance literature, the type of agency costs can vary depending on the ownership and control structure of a corporation, whether ownership and control are dispersed or concentrated. For corporations with diffuse share ownership, where the day-to-day functioning of a corporation is entrusted by the shareholders (the principal) to managers (the agent), so that there is separation of ownership and control, the agency problem is dubbed Type I or vertical agency problems. Such corporations, termed as widely held, are typically present in the United States and the United Kingdom. In contrast, for corporations characterized by concentrated share ownership and control, agency problems arise between two categories of shareholders or principals, namely the inside shareholders with substantial equity stakes and management control, and dispersed minority shareholders, the agency problem is dubbed as Type II or horizontal agency problems (Roe 2004). Under Type II problems, as Morck and Yeung (2004) argue, controlling shareholders have incentives to opportunistically extract and optimize private benefits for

76

J. Sarkar

themselves at the expense of the outside minority shareholders. Although minority shareholders are entitled to the cash flow rights corresponding to their share of equity ownership, they face the uncertainty that an entrenched controlling owner may opportunistically deprive them of their rights through various means (Claessens and Fan 2002). Corporations with Type II agency problems are the rule rather than an exception in Asian economies including India, Latin America, and Continental Europe. Further, by virtue of the inherent structural characteristics of family-based business groups, Type II agency problems are particularly endemic in groups as opposed to independent firms with concentrated ownership and control. For the latter, concentrated ownership can bring about greater goal congruence between the controlling insider shareholders and the minority outside shareholders, but as have been discussed extensively in the literature, a business group with a network of independently incorporated firms, and interconnected through a web of shareholdings, can enable the manifestation of Type II agency problems (Morck and Yeung 2004; Masulis et al. 2011; Gilson 2006). In business groups, Type II agency costs through opportunistic behavior of controlling shareholders can manifest in several forms depending on the type of controlling owners (Cronqvist and Nilsson 2003), and the type of controlling devices, namely, either through substantial equity investments or through structural devices like dual class shares and stock pyramids (Gilson 2006). In family-owned business groups, as Bautista (2002) observes, owing to the dominance of family members in management and non-transparency in functioning, minority shareholders are “often kept in the dark” regarding the actual performance of the corporation. Expropriation of minority shareholders in family-owned business groups can also happen through structural mechanisms like stock pyramids where a family firm A, having a majority ownership in a publicly traded firm B, can control a publicly traded firm C in which A has no direct ownership but in which B has a majority ownership. A linking of equity ownership between firms through pyramids can therefore drive a wedge between control rights and cash flow rights and gives the shareholder of A, a vehicle for the expropriation of minority shareholders of D to transfer assets and profits from firms with lower cash flow rights (i.e., from D) to firms with higher cash flow rights (i.e., to A) (La Porta et al. 1999). Such a phenomenon, referred to the literature as tunneling, essentially involves self-dealing transactions that remain undetected by minority shareholders and regulators alike, such as outright theft or fraud, underor over-invoicing of asset, goods, or services sales, obtaining loans on preferential terms, transfer assets from listed companies to unlisted companies and through preferential pricing of fresh equity (Johnson et al. 2000). There is ample evidence in the extant literature that business groups are typically organized as pyramids and that there are divergences between control rights and cash flow rights of controlling shareholders (Claessens and Fan 2002; Faccio and Lang 2002; Masulis et al. 2011)). For instance, Masulis et al. 2011), in analyzing the control and financing structure of family business groups in 45 countries around the world, find that two thirds of these groups are set up as pyramids with listed firms used to a different extent to separate group members from the ultimate owner. Evidence on tunneling in pyramidal structures are however relatively limited. Given

4 Ownership Control and Board Governance of Indian Business Groups …

77

that tunneling by design is clandestine, researchers have tried to empirically ferret out such activities through various proxies (see for example, Bertrand et al. 2002 for India; Claessens and Fan 2002 for East Asia; Cheung et al. 2006 for Hong Kong). Finally, while pyramidal structures contribute to ownership complexity in business groups and manifest in Type II agency problems, an additional and related source of such complexity that can potentially facilitate the expropriation of minority shareholders is the opacity of insider control (Sarkar and Sarkar 2012). The term opacity seeks to capture incomplete information on the ownership control webs that link firms either through pyramids or through cross-holdings (firms mutually having equity stakes in each other), to the extent that outside investors of listed firms or regulators are unable to decipher from publicly disclosed information on shareholding patterns, the complete chain of control among group affiliates and the benefits that flow to the ultimate owner(s) of a group and its constituent firms. Lack of information on such control webs can be an important source of agency costs as it can help conceal the diversion and flow of expropriated funds. Several types of ownership opacity can be relevant for business groups depending on the regulatory disclosure requirements on equity holdings. One could be the incomplete disclosure of the identity of insider owner(s) (Type I opacity), two, the fragmentation of insider ownership across a large number of owners (Type II opacity), and three, the extent to which inside ownership and control are in the hands of private unlisted entities for which disclosure requirements are limited (Type III opacity). With regard to Type I, if disclosure rules require the reporting of only those stock holdings that cross a particular threshold, ownership structure can be strategically engineered by controlling shareholders through the fragmentation of shareholding whereby individual ownership by insiders could be deliberately kept at less than one percent to avoid mandatory disclosures. The larger the percentage of shareholding in the less than one percent cut-off and outside the public domain, the more opaque could one consider the ownership structure to be from the point of view of an outsider. Type II stems from the extent to which insider shareholding could be “fragmented” among its constituents; distributing a given shareholding among a large number of insiders again could potentially be an obstacle to efficient monitoring and raise transaction costs. Finally, related to Type II opacity, Type III opacity accounts for the class of promoter shareholding, namely individuals, listed companies, and unlisted companies and trusts. The more the weight of such shareholding is toward unlisted companies and trusts, the more unlikely would it be for an outside minority shareholder, to decipher chains of control as well as any related party transactions. The ownership network can become all the more complex if cross-holdings by such private companies in group affiliates. Given the discussion on the nature of the governance problem in business groups, Sects. 4.4.2 and 4.4.3 presents some key analyzes on ownership and control structures in Indian business groups. The analysis is based on the panel data on Indian group affiliates and standalones for the period 2005 to 2018, as referred to in the introduction.

78

J. Sarkar

4.4.2 Concentrated Ownership and Control in Indian Business Groups Historical accounts testify that from the very early years of business group formation in India, such groups, along with their affiliates were characterized by concentrated ownership and family control together with pyramidal ownership structures as well as cross-holdings (See for example, Hazari 1966). Further, governance issues in these groups could be clearly understood from an agency-theoretic/corporate finance perspective as outlined in the previous section. The ownership and control structure in the formative years of Indian business groups was a natural consequence of how companies under Indian ownership were financed at a time when stock markets were thin, and the banking system was weak. The growth of companies during that period was largely financed from retained earnings and from non-institutional sources, i.e., funds borrowed from family members, close business associates, social contacts, and money lenders (Tripathi 2004). With a major source of finance originating within the family, formal ownership and control of the companies were often accomplished through the setting up of joint stock companies legally, where family members and acquaintances were issued shares to retain family control. A family member could therefore control a group of companies, either through direct equity control (the “inner circle”) or through indirect control through companies that were under its direct control (the “outer circle”) (Hazari 1966). This was the beginning of concentrated ownership and control of family-owned business groups in India. Individuals who were instrumental in floating and developing the various ventures, which were eventually incorporated as joint stock companies, came to be known as “promoters.” As Lokanathan (1934) observes, Indian promoters were not typically the professional promoters who focused mainly on starting a business but not necessarily developing it further. Instead, promoters in Indiahad substantial financial interests in the concerns that they floated, and organized themselves as managing agents, taking it upon themselves the entire gamut of functions ranging from pioneering, to promoting, to financing to managing the concerns while retaining control over them (Lokanathan 1934). The presence of minority outside shareholders too can be traced back to the early years of group formation. When external finance was raised by companies by managing agencies through initial public offerings, these were invariably oversubscribed (Lokanathan 1934; Hazari 1966; Goswami 2000) so that the shares at the time of allotment were split into small lots to the extent that no single shareholder, other than the managing agency, would have enough stakes to exercise control over the company in terms of their presence on the board of directors. De facto control of the company by managing agents with stock ownership could be achieved with as little as 10% (Goswami 1989). With ownership by outside shareholders fragmented and dispersed, investments by promoters were made, not based on efficiency considerations, but to serve the purposes of controlling interests. This was reportedly undertaken via the setting up

4 Ownership Control and Board Governance of Indian Business Groups …

79

of companies that could facilitate in the purchase of their own shares indirectly as also enable them to transfer profits and losses among group companies (Hazari 1966). Apart from direct equity control, indirect control of firms was acquired through interconnected equity holdings among affiliates through a combination of pyramiding and cross-shareholdings/circular chains of investments (Hazari 1966; Mehta 1955). Equity control in turn ensured management control, allowing managing agents to sit on company boards. Such integration of control and ownership structures was characteristic of both European corporate groups as well as Indian business groups (Mehta 1955). For Indian concerns, the practice of appointing family members at higher levels of the management hierarchy irrespective of their capabilities adversely affected efficiency and led to “glaring abuses” of minority investors (Hazari 1966).6 Explicit concern for minority investors is also found in several narratives documented in a review in the late fifties of the working of the managing agency system (NCAER 1959).7 The preceding account clearly affirms that business groups in India in their early years were characterized by Type II agency problems, between the controlling insiders and minority shareholders. As with the persistence of business group dominance in private corporate sector activity (Sect. 4.4.3), the ownership and control structure of business groups and their affiliates have also been path-dependent even to the extent that the nomenclature of promoters to refer to inside owners have persisted till the present, in regulatory and legal parlance such as in securities market regulations and company law. With regard to the company law, for instance, both the terms “promoter” and “control,” have been defined under the Companies Act 2013. Under Section 2(69), a promoter shall be any of the following persons (a) whose name appears as a promoter in the prospectus or annual return or (b) who, directly or indirectly has the control over affairs of the company either as a shareholder, director or otherwise or (c) A person in accordance with whose advice, directions, or instruction the board of directors of the company is accustomed to act. However, any person who is acting merely in a professional capacity cannot be considered as a promoter under (c).8 Section 2(69) must be read with Section 2(27) which defines “control” under the 6

For instance, Mehta (1955) estimates that as of the early fifties, nine leading families of India held 600 directorships or partnerships in Indian industries, about 100 persons held as many as 1700 directorships, and finally, the top 10 industrialists held together around 400 directorships. Such high estimates have been argued to be a fallout of the dearth of managerial talent in India in the early years of industrialization and also a result of the high level of concentration of ownership and control exercised through the managing agency system. 7 For example, as part of parliamentary debates in 1951–52, a parliamentarian, Shri Tyagi remarked that “…the primary object in acquiring control over management has not been the progressive expansion or development of those undertakings but the furtherance of the personal advantage of certain people, to the detriment of investors and the interests of the companies themselves” (NCAER 1959; pp. 8–9). 8 It may be noted that while the earlier company law, Companies Act 1956 included the term promoter, it did not formally define it, the term was explained under clause (a) of sub-section (6) of the section 62 Companies Act, 1956 stated that “the expression “promoter” means a promoter who was a party to the preparation of the prospectus or of the portion thereof containing the untrue statement, but does not include any person by reason of his acting in a professional capacity for

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Act. Under the latter provision, “control shall include the right to appoint majority of the directors or to control the management or policy decisions exercisable by a person or persons acting individually or in concert, directly or indirectly, including by virtue of their shareholding or management rights or shareholders agreements or voting agreements or in any other manner.” As with the Companies Act 2013, the terms promoters and control have also been defined by the SEBI for listed companies as under Regulation 2 (1) (za) of SEBI (Issue of Capital and Disclosure Requirements) Regulations, 2009. Likewise, AS-21 of the Accounting Standards has also defined “control” for the purpose of consolidation of financial statements. A careful reading of the various definitions of the terms promoter and control will reveal that while some of the wordings may differ, the basic essence of the definitions is the same. Finally, it is important to note that neither of the terms have been defined in the specific context of a business group or group affiliates and are applicable to all companies irrespective of their ownership status. Turning to an analysis of the structure of ownership and control in business groups and group affiliated firms, Table 4.4 presents the ownership structure of Indian private sector listed firms, those that are affiliated to business groups and those that are standalones for the year 2018, as disclosed under Regulation 31 of the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015 under which listed entities are required to disclose their shareholding pattern under a prescribed format. As is evident from the Table, promoters in group affiliates on an average held majority stakes, 54.63% of total shareholding, whereas those for standalones was a little short of majority of 49%. Thus, irrespective of whether a firm is affiliated to a group or not, ownership is concentrated in the hands of promoters or insiders. However, if one compares the composition of promoter ownership in terms of the types of promoters, we find a noticeable difference between group affiliates and standalone; for the former, the share of promoters as corporate bodies is on an average nearly 40% as compared to around 24% for standalones. Further analysis can reveal whether the greater presence of corporates within the promoter group for group affiliates is on account of other affiliates within the group holding equity positions in an affiliate. Considering outside shareholders as listed under non-Promoters, one finds that there is not much difference in the composition between group affiliates and standalones. It is to be noted that, going by the standard cut-off of 20% ownership that is applied to define control in the literature, barring non-institutional individuals, who are essentially dispersed outside shareholders, and cannot be considered as a controlling block, none of the other constituents under the non-promoters, be these mutual funds, banks, or financial institutions, have controlling stakes on an average. To examine whether the structure of ownership is substantially different for the affiliates of the top ten groups (Table 4.2) as compared to the average ownership structure across all group affiliates, comparative estimates are presented in Column (5) of Table 4.4. As is evident from the Table, while average promoter share in the top persons engaged in procuring the formation of the company.” https://www.icsi.edu/media/portals/ 86/Geeta Saar 38 Promoter and Control Part-1.pdf.

4 Ownership Control and Board Governance of Indian Business Groups …

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Table 4.4 Composition of share ownership of Indian companies: 2018 Group affiliates

Stand alone

All

Group affiliates (Top 10 groups)

(1)

(2)

(3)

(4)

(5)

A. Promoter and Promoter Group

54.63

49.33

52.07

54.47

Individuals/HUF

12.31

29.35

20.79

2.37

Bodies corporate

39.66

24.12

33.44

45.04

Government

0.26

0.06

0.17

1.35

4. Financial Institutions and Banks

0.08

0.11

0.09

0

5. Indian Promoters Others

2.28

2.29

2.28

2.49

6. Foreign Promoters

4.33

3.43

3.90

4.71

B. Non-Promoters

45.64

51.01

48.24

46.37

Mutual Funds

3.97

3.01

3.58

4.45

Banks and Financial Institutions

1.59

2

1.78

1.43

Government

0.21

0.05

0.13

0.54

Non-Institutional Corporate Bodies

7.76

9.68

8.67

5.08

Non-Institutional Individuals

21.29

28.25

24.65

15.68

Non-Institutional Others

3.17

4.28

3.71

3.37

Source Author’s computation based on the Prowess database

10 affiliates is comparable to the overall mean for group affiliates, the composition of promoter share is noticeably different; the share of individuals/Hindu Undivided Family (HUF) is strikingly less, at 2.37 as compared to 12.31% for all affiliates, whereas corporate bodies have higher holdings in the former as compared to the latter. Thus, much of the promoters in affiliates of large groups are corporate entities rather than individuals. While understanding the structure of ownership of group affiliates and standalones in terms of average equity holdings of the key shareholding group provides some overall picture of the incidence of insider control, it is important to delve further into the distributional characteristics of promoter ownership in both group affiliates and standalones. Given that the level of ownership of any shareholder or a block of shareholder is associated with voting rights and control, and with promoters being the single largest block in group affiliates, it is important to find out the distribution of group affiliates by different blocks of promoter ownership. Drawing on the relevant literature on ownership and governance on how voting rights can change

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with ownership, we break-up the promoter ownership of Indian affiliates into the following blocks, namely holdings of greater than zero and less than 5% (Block 1), between 5 and 10% (Block 2), between 10 and 20% (Block 3), between 20 and 26% (Block 4), between 26 and 51% (Block 5), between 51 and 75% (Block 6) and greater than 75% (Block 7). In the Indian context, shareholders with a minimum of 10% paid-up voting capital can call an extraordinary general meeting. A cut-off of 20% is typically the minimum level of equity ownership that is necessary to control a corporation (La Porta et al. 1999) and if corporations are relatively large in size, it is likely to have a larger base of dispersed shareholders and hence insiders can gain effective control with even lower levels equity. A stake of 26% or more under the Indian company law entitles a shareholder to block special resolutions and have a say in the management of a company. A 51% shareholding gives a majority stake and allows wide control over the management of the firm but is subject to a blocking minority, and a stake of more than 75% is not subject to a blocking minority and important corporate decisions, such as proposed mergers, altering memorandum and articles of association requires 75% in favor. The distribution of firms across the different blocks of promoter share is presented in Fig. 4.4. The estimates in the Figure are striking in terms of the overwhelmingly large number of companies, both standalones and group affiliates with majority control by promoters; almost 62% of group affiliates and 55% of standalones have promoters with equity ownership in Block 5, i.e., between 51 and 75%. This is followed by Block 4, where close to 30% of group affiliates and standalones have equity ownership between 26 and 51%. If 20% is taken as equity ownership with effective control, then as of 2018, strikingly in almost 96% of group affiliates and 90% of standalone promoters or insiders have effective control. This is much higher than comparable estimates for insider control in other countries using the 20% cutoff—50% documented in La Porta et al. (1998) and Claessens and Fan (2002). 70

61.97

60

55.17

50 40 29.82 27.88

30

20 10

1.04

3.41

0.95 1.95

2.33

5.09

2.25 4.42

1.64 2.08

0 12

11

27

percent of group affiliates

26

345

717

19

per cent of standalones

Fig. 4.4 Distribution of firms by promoter share: 2018. Source Author’s computation from the Prowess database

4 Ownership Control and Board Governance of Indian Business Groups …

83

4.4.3 The Persistence of Concentrated Ownership and Control With a dynamic institutional and economic environment since the late nineties well into the 2000s, one needs to examine whether there have been any major changes in the shareholding structure of group affiliates over time, or whether there is persistence too in this regard. During the period under study, 2005–18, several major legislative and regulatory changes have been instituted including a new company law, Companies Act 2013 repealing Companies Act, 1956, the Substantial Acquisition of Shares and Takeovers Regulations, 2011, repealing the earlier 1997 regulations, continuous strengthening of disclosure standards for listed companies by the SEBI, as well as changes in the entry of foreign institutional investors, could have led to re-optimization of equity portfolios of the different types of shareholders. To this end, the analysis in this section will, one, examine the trends in the components of the aggregate ownership for listed group affiliates for the period 2006–2018, and two, examine trends during the same period in promoter shares for different groups as measured by their size. Figure 4.5 presents trends in the ownership structure of group affiliates between 2006 and 2018. As can be seen from the Table, promoter ownership since 2006 up until 2013, increasing steadily from 49% and crossing the majority mark in 2009. Thereafter, promoter holdings have stabilized around 54% all the way up to 2018. No clear trend is discernible for the other owners except for banks and financial institutions steadily decreasing their already limited holdings from around 4% in 2006 to being consistently below 3% after 2015. The overall impression that one gets from Fig. 4.5 is that the predominance of promoter control in group firms has persisted over a span of 12 years irrespective of structural changes from time to time in the institutional environment. If one takes an even longer time frame, back to 2001, this pattern seems to have been the same of a steady consolidation of promoter ownership while other blockholders showing marginal changes at best (Sarkar and Sarkar 2012). While Fig. 4.5 provides a broad-brush picture of the trends in equity ownership over more than a decade, by major types of owners, Fig. 4.6 takes a close look at whether the consolidation that one finds in insider control on an average across all group affiliates has also happened across groups of different sizes. The analysis of group characteristics in Sect. 4.2 reveals that there is substantial heterogeneity among groups in terms of their asset size and that is there are few large groups at one end of the spectrum and a large tail of small groups at the other end. Has there been consolidation of promoter ownership in the larger groups with a larger network of affiliates where the scope of Type II agency costs can be expected to be higher, or is it the smaller groups with a fewer number of firms and activities where such consolidation has taken place? From an agency perspective, greater consolidation of insider ownership on an average in a group is not necessarily harmful for outside investors; it brings about greater convergence of interests between the insiders and outsiders, and hence would mitigate Type I agency costs. However, at the same time,

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60.00 50.00 40.00 30.00 20.00 10.00 0.00 2006

2007

2008

2009

2010

2011

Promoters

2012

2013

2014

2015

2016

2017

2018

Mutual Funds

Banks and Financial Institutions

Foreign Institutional Investors

Corporate bodies

Individuals

Others

Fig. 4.5 Trends in shareholdings in group affiliates by major types of owners: 2006–2018. Source Author’s computation from the Prowess database

higher insider holdings can aggravate Type II agency costs through the entrenchment of insiders who by virtue of higher control, can successfully insulate themselves from outside disciplining forces such as that from the takeover market or managerial labor market (Demsetz 1983; Fama and Jensen 1983) and can exercise greater control through pyramids and other mechanisms to expropriate minority investors. It is not therefore a priori clear whether greater consolidation aggravates or mitigates agency costs. Turning to the analysis in Fig. 4.6, based on the distribution of group size, seven size classes of business groups are considered by percentile values (denoted by P) as shown in the graph, with P < 25 are groups lower than the first quartile of the distribution, P25-P50 being groups falling between the first quartile and median, and so on. Several observations can be made from the figure. First, as with the case of all affiliates, average promoter shares across all groups irrespective of size have risen by 4 to 6%age points during 2006–2018, with much of the percentage increase happening by 2012, post which promoter holdings of all groups on the average have exceeded the majority mark of 51%. Second, if one compares the average promoter holdings by size classes, by and large there is an inverse relationship between group size and average promoter holdings of a group. The promoter’s share of smaller groups is greater than that of the larger groups: this is along the expected lines as larger groups with larger firms on the average typically have a higher proportion of outside shareholders. But from the perspective of control, such differences in

4 Ownership Control and Board Governance of Indian Business Groups …

85

60

58 56 54 52 50 48 46 44 42 40 2006

2007 P=P99

Fig. 4.6 Trends in promoter ownership by group size: 2006–2018. Source Author’s computation based on the Prowess database

the case of Indian business groups do not seem to matter as groups, across all size classes, post 2012 have majority insider ownership. Third, trend estimates across groups show that between two end points of the period of analysis, 2006 and 2018, promoter consolidation has been the highest for the smallest two groups.

4.4.4 Ownership Complexity As discussed in Sect. 4.1, agency costs in business groups are manifested not only in terms of concentrated ownership and control by insiders, but on account of complexities in group structure arising from stock pyramids, cross-holdings, and opacity of ownership. This section presents some measures of ownership complexity in Indian business groups and how these can vary across groups in terms of examining for the year 2018, the intra-group distribution of promoter ownership for the top ten groups, mapping out the group structures of the top two groups, the Tata Group, the Reliance Group (Mukesh Ambani), and the Adani Group to identify the existence of pyramidal structures and cross-holdings if any, and to present some measures of ownership opacity based on firm level data of major promoters reported in the Prowess database. Table 4.5 presents the distribution of promoter ownership for the top ten groups as of 2018. The estimates are presented at different percentiles (denoted by P), starting with the minimum, followed by the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentile and the maximum shareholding in a group. As can be seen from the estimates, promoter share differs considerably across firms within a group, the range between the lowest and the highest being substantially different for several of the groups. For 80% of these groups, the median shareholding is more than 51%.

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Further, the variations in promoter ownership within each group imply that theoretically tunneling incentives exist if the firms are structured as pyramids, with firms where promoters have the highest cash flows located at the top of the pyramid. All that is necessary for pyramidal structure to generate tunneling incentives is that the firm at the top of the pyramid has controlling rights on the firm below it, and the second firm has controlling rights on the firm below it and so on. With a typical cut-off 20% for a controlling stake, one can see from the estimates in Table 4.5 that promoters have controlling stakes even where their shareholder is at the minimum across all group firms. While one cannot for certain conclude from the dispersion in promoter share that groups are necessarily organized as pyramids, Masulis et al. (2010) have estimated that the percentage of Indian group affiliates that are controlled through pyramids is around 10%, the average pyramidal layer being 0.36 and the percentage of market of capitalization held by pyramid-controlled firms is 4.10. The complexity of ownership and control structures and its variation across business groups can be illustrated from an analysis of the Tata Group, the oldest of all business groups, the Reliance Group (Mukesh Ambani) which emerged in the eighties, and the Adani Group, which emerged in the nineties, and which entered the ranks of the top ten business groups in recent years. These are presented in Fig. 4.7a–c. All the structures mapped are based on only the listed companies in a group for which shareholding information is present in the public domain; including the holdings of all unlisted companies in each group would increase the complexity of shareholding manifold. Focusing on the Tata Group, it is evident from Fig. 4.7a that Tata Sons is the main holding company of the Tata Group which is privately held and has controlling direct stakes in all major group listed companies including that in the group’s flagship Table 4.5 Distribution of promoter ownership of top ten groups: 2018 Promoter Share Min

P5

P10

P25

P50

P75

P90

P95

Max

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

Reliance (M A)

36.45

45.43

45.43

45.43

46.44

47.45

47.45

47.45

75

Tata

30.3

30.80

32.61

34.12

50.09

71.92

74.96

74.99

75

Aditya Birla

34.68

34.68

34.68

40.10

47.07

61.98

74.03

74.03

74.03

Reliance (A A)

49.54

49.54

49.54

50.89

52.66

64.05

75.00

75.00

85.76

Larsen and Toubro

64.01

64.01

64.01

64.01

64.01

64.01

64.01

64.01

88.81

O. P. Jindal

41.75

41.75

41.75

53.59

58.66

62.32

74.99

74.99

74.99

Bharti

53.51

53.51

53.51

53.51

60.33

67.14

67.14

67.14

67.14

Vedanta

50.13

50.13

50.13

50.13

54.03

64.92

64.92

64.92

64.92

Adani

66.27

66.27

66.27

66.27

73.07

74.92

74.92

74.92

74.92

Bajaj

15.43

15.43

44.32

49.30

55.14

66.86

69.61

73.12

73.12

Notes P denotes percentile Source Author’s computation based on the Prowess database

4 Ownership Control and Board Governance of Indian Business Groups …

87 Tinplate Company

74.96% 6.48%

(a)

Tata Teleservices Maharashtra

Tata Power

Tata Steel Long Products

48.30%

TIL 31.05%

54.50%

19.58%

2.50 %

54.45%

Tata Steel

Tata Motors

Tayo Rolls

50.09%

Tata Teleservices Ltd

Tata Metaliks

31.64 %

33.30%

0.07%

Titan

20.84% Voltas Ltd 26.64%

3.01%

Tata Elxsi Ltd

India Hotels Company Ltd

TATA SONS

42.22%

36.43%

2.34%

71.89% 23.47% 27.74%

TCS

Tata Chemicals

30.38%

Trent Ltd

Tata Global Beverages

0.11%

14.07% Tata Comm Ltd

Tata Chemicals 68.14%

0.29%

0.45%

0.07%

TICL

0.86%

0.04% 1.58%

0.04%

Ewarts

Sri Ratan Tata Trust Trent Brands Ltd

1.56%

Af-taab Investment

Fig. 4.7 a Ownership Structure of the Tata Group: 2018. b Ownership Structure of the Reliance Group (Mukesh Ambani): March 2018. c Ownership Structure of the Adani Group: March 2018. Source Author’s compilation based on shareholding pattern for quarter ending March 2018, as reported in the Prowess database

company Tata Steel. The Figure also illustrates a single layered pyramid flowing from Tata Sons to Tata Steel to four other listed companies. Cross holdings can also be identified in the group structure between TICL and Trent Limited. Moving on to the structure of the Reliance Group (Mukesh Ambani), (Fig. 4.7b), the structure is fundamentally different from the Tata Group. By virtue of having much lesser number of listed companies, the structure looks less complex than that of the Tata

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J. Sarkar

(b) Individuals 6 Welfare Association

Pvt ltd and LLPs 39

Figure 0.69% 0.08% 42.7%

Reliance Industrial Infrastructure Ltd

Petroleum Trust

RIL 45.43%

3.91%

(c)

S.B. Adani Family Trust 56.48%

Adani Tradeline LLP

9.05%

Gautam Adani Family Trust Afro Asia Trade & Investment Ltd

2.75%

Adani Enterprise Ltd

0.08%

0.34%

1.47%

Adani Green Energy Ltd

0.25%

2.75% Worldwide Emerging Market Holding Ltd

Pan Asia Trade and Investment Pvt Ltd

3.82%

2.75%

0.34%

Adani Power Ltd

4.43% 2.75% Adani Ports & SEZ Ltd

Adani Gas Ltd

2.75% Adani Transmission Ltd

2.75%

2.75%

3.90% Universal Trade & Investment Ltd

Fig. 4.7 (continued)

5.00%

4 Ownership Control and Board Governance of Indian Business Groups …

89

Group. However, unlike that of the Tata Group, there is a preponderance of private limited companies on which information is scarce in the public domain, and a greater fragmentation in promoter holdings, contributing to ownership opacity. Finally, the ownership structure of the Adani Group (Fig. 4.7c) is dominated by a large number of private limited companies as is the case with the Reliance Group. What is different however from the Reliance group is the controlling holdings of family trusts in the flagship listed company Adani Enterprises. Both in the case of the Reliance Group and Adani Group, unlike the Tata Group, the ownership of the major listed companies is all in the private domain, as also the fact that there is no information on how these private companies and the trusts are interconnected. Examining the different types of opacity for Indian listed companies, Type I opacity has almost been eliminated due to a change in disclosure regulations since April 2006, which required the identity of all constituents of promoters and promoter group along with their respective shareholdings to be disclosed to the stock exchanges under SEBI regulations. Prior to this period, the presence of such opacity was documented by Sarkar and Sarkar (2009). With regard to Type II and Type III opacity, Table 4.6 presents a detailed picture of such opacity for the flagship companies of the top three business groups as of 2018, namely Reliance Industries Limited of the Reliance Group, Tata Steel of the Tata Group, and Hindalco Industries of the Aditya Birla Group. As can be clearly seen from the Table, the different manifestations of Type II and Type III opacity are in-built in the ownership structure of these companies, but to different extents. In case of Type II opacity, Reliance Industries had as many as 47 entities listed under promoters and promoter group with a total equity share of 47.45%, which came to be an average share of only 1.01% per promoter. The corresponding estimates for Tata Steel and Hindalco Industries were around 2.76 and 2.03%, respectively, all three lower than the average of 4% obtained for the total sample of group affiliates for the year 2018. Further, what is of interest to note is that except for Tata Steel, more than 50% of promoters belong to unlisted companies, trusts, and individuals, the highest being for Reliance Industries, at around 85%. With regard to percentage of equity holdings by the three types of promoters, as Panel B shows, unlisted companies and trusts overwhelmingly account for promoter equity in the case of Reliance Industries (98%), and Hindalco Industries (85%) and Tata Steel (95%).

4.5 Insider Control and Board Governance The pervasiveness and persistence of promoter ownership and control in Indian business groups evident from the detailed analysis in the previous section underscores the important role that board of directors can play in the mitigation of Type II agency costs in such groups. One of the governance mechanisms that is proposed in the literature as a prescription for reducing agency costs focuses on the positive role that outside blockholders with relatively large equity positions can play in disciplining inside management. Dubbed as the “efficient monitoring hypothesis,” (Berle and

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Table 4.6 Promoter ownership characteristics in selected companies: March 2018 Reliance Industries

Tata steel

Hindalco industries

A. Number of promoters by type All

47

12

17

– Individuals

6

0

5

– Listed Companies

1

10

3

– Unlisted Companies and Trusts

40

1

9

47.45

33.21

34.67

% B. of holdings by promoter type All – Individuals

0.69

0.00

0.11

– Listed Companies

0.01

1.57

5.25

– Unlisted Companies and Trusts

46.75

31.64

29.31

1.01

2.76

2.03

C. Average Promoter Holdings by Promoter Type (B/A) All – Individuals

0.11

–

0.02

– Listed Companies

0.01

0.16

1.75

– Unlisted Companies and Trusts

1.17

31.64

3.26

Notes “A” lists the number of promoters constituting Promoters and Promoter Group as well as the number of each type of promoter (individuals, listed companies and unlisted companies and trusts). “B” lists the total percentage shareholding by promoter type, i.e., the percentage equity holding by promoters who are individuals etc. “C” is the average holding by type of promoter Source Authors’ computation based on the Prowess database and www.corpfiling.co.in

Means 1932; Pound 1988), the basic premise of the hypothesis is that large outside shareholders, unlike small, dispersed shareholders, are likely to exercise optimal oversight on the insiders as they have substantial investments at stake as well as the voting power to ensure that the investments are not lost (Fama and Jensen 1983; Shleifer and Vishny 1997). In this regard, the literature highlights specifically the role of institutional investors in bringing about collective action against the management should it stand in the way of shareholder value maximization (Dodd and Warner 1983). However, as the estimates of shareholding by outside shareholders in Indian companies, as under nonpromoters, reveal, the holdings by outside institutional blockholders, namely, mutual funds, banks, and financial institutions, fall far short of the controlling shareholding even if all institutional holders act as a block together. On the other hand, promoters, the inside blockholders, have majority holding in more than 90% of groups/group affiliates. Empirical evidence on the effect of outside blockholders on firm performance in the case of Indian firms, including group affiliates have yielded mixed results, with some studies find no evidence of efficient monitoring of promoters (Khanna and Palepu 2000; Douma 2006), whereas Sarkar and Sarkar (2000) and Kumar (2008) find a positive effect of banks and financial institutions once their

4 Ownership Control and Board Governance of Indian Business Groups …

91

equity positions cross a particular threshold. The likelihood of outside blockholders not being efficient monitors of insiders, owing to non-controlling stakes, coupled with the fact that other external governance channels like the market for corporate control is likely to be weak in the face of consolidated promoter equity positions, puts the burden of monitoring on another disciplinary mechanism, that of the board of directors.

4.5.1 Monitoring by the Board As laid down in the Cadbury Report on corporate governance (Cadbury 1992), directors on a company board are fiduciaries of shareholders and other stakeholders and should therefore act in their interest. Directors on boards have both a strategic role and a monitoring role; under the former, the responsibility is to define a company’s purpose and to draw up plans to achieve that purpose, and under the latter, to monitor and assess the performance of the management and execute, if necessary, the power to replace the chief executive and/or internal management team. The monitoring and disciplining responsibilities of the board of directors depend on the nature of the agency problem, Type I or Type II, which is slated to mediate (Roe 2014). While the board acts as an intermediary in both cases, the nature of the agency problem it mediates and associated problems of monitoring and disciplining that it addresses are different. Under Type I agency problems, with complete separation of management and control and given the inability of diffused shareholders to monitor, the board’s responsibilities are that of “vertical governance” that entails working on behalf of the shareholders to minimize managerial opportunism and maximize shareholder wealth. On the other hand, a board is engaged in of “horizontal governance”, of mediating between the dominant shareholders who in all likelihood also have management control, and the outside minority shareholders and shield the latter from being expropriated by the former. Thus, in this case, the focus of board functions would be more on preventing self-dealing transactions by the management than on shirking by managers as is the case under Type I problems (Roe 2004). The governance by the board of directors of firms with concentrated ownership and control is further compounded by the presence of promoters in management positions, including occupying the positions of a CEO or Chairperson or both. CEOs from the founding family are found to be more influential in decision-making (Finkelstein 1992). Such CEOs can have a say in the composition of the board on the one hand and are more likely to be in management control on the other, so that much greater potential exists for “board capture,” “CEO hegemony” or the creation of an “inner circle.” Non-executive directors on boards of such firm may therefore require different strategies and skill sets as well as incentives to impart their fiduciary duties

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of monitoring and advising management (Anderson and Reeb 2004; DeMott 2007).9 For them, the problem of governance in family firms is to balance the conflicting interests of the two major blocks of shareholders, controlling insiders and minority outsiders rather than aligning the interests of the manager and shareholders to maximize shareholder value as is the case with non-family firms. Thus in family firms, in order to protect firm value, independent directors would have to be extra vigilant to guard against the expropriation of assets by a controlling shareholder (DeMott 2007; Claessens and Fan 2002; Maury 2006). A critical aspect of the quality of board governance of any firm, irrespective of its ownership status is the “busyness” of its directors, both inside directors and outside directors. A director is construed as being busy if she/he holds directorial appointments in other firms to the extent that such multiple directorships can make directors over-committed and thereby compromise on their ability to monitor company management effectively on behalf of the shareholders (Ferris et al. 2003). On the other hand, busy directors can be potentially beneficial as the number of multiple directorships can proxy for high director quality (Fama 1980; Fama and Jensen 1983). Further, from a resource dependency perspective, directors with multiple appointments, by virtue of being more networked, can generate benefits by helping to bring in needed resources, suppliers, and customers to a company (Pfeffer 1972; Booth and Deli 1996). Being firms affiliated to a business group can have implications for the costs and benefits associated with busyness. As Sarkar and Sarkar (2009) contending the context of group affiliated firms in India, multiple directorships could be on account of multiple positions in companies belonging to a single group. In particular, inside directors belonging to founding families, i.e., promoter directors are likely to sit on the boards of other group affiliates with the purpose of collective coordination, overall supervision, and control. Likewise, independent directors may have their directorships concentrated within a particular group and form an “inner circle” of the group’s management team. Thus, boards of group affiliates could end up with a set of closely related core leaders with duplicating positions in affiliates and vested with major responsibilities. While group-centric multiple directorships can be associated with benefits too, stemming from goal congruence and group synergy (Ouchi 1980), it can also create additional scope for promoters to engage in nepotism or kinship and to fill up member firms with friendly faces, thereby leading to promoter hegemony. Evidence of group centric multiple directorships is found for a sample of 1704 listed Indian firms for the year 201810 ; directors on an average have around 72% of their directorships in group affiliates with 42% of directors having all their directorships in only group companies. With regard to inside directors including promoters on 9

A case in point is that independent directors in family firms are required to be one of the “primary lines of defense” for minority shareholders to guard against expropriation by controlling shareholders (Anderson and Reeb 2004). 10 Author’s estimates based on the Prowess database. Earlier estimates of group centric directorships pertaining to the year 2003 are found in Sarkar and Sarkar (2009).

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board, an overwhelming majority of around 80% of their directorial positions are in group affiliates. Of these positions held by inside directors in group affiliates, 81% are found to be within the same group where the director acts as an insider director of one of its affiliates. In contrast, relatively few inside directors of non-affiliates or standalones occupy a directorial position as an outside director in group affiliates. What is further telling is that a similar picture of group-centric positions holds for independent directors.

4.5.2 Board of Directors: The Evolving Corporate Governance Framework in India In India, the rules and regulations that determine the composition and functioning of corporate boards to enable directors to exercise their fiduciary duties to the shareholders have historically been laid down in company law. Prior to the initiation of corporate governance reforms in India in the late nineties, other than the relevant provisions in company law, there was little by the way of a comprehensive and consistent set of laws and regulations that would come under the ambit of corporate governance. However, historical accounts of the evolution of the corporate form and that of business groups (see Khanna 2005; Tripathi, Mehta 1955; Goswami 2007) do mention the existence of a governance framework in terms of the institution of the managing agency system, the existence the centralization of management with delegation of powers, the appointments of professional managers, and powers and fiduciary responsibilities of the board of directors. As Goswami (2007) states, as the corporate sector grew in the colonial era, corporate law was put in place early on through the Companies Act 1913, which formed the foundation of the later Companies Act 1956 and Companies Act 2013. Issues of corporate governance and the need for reforms came to the forefront in the second half of the nineties following the adoption of structural adjustment and globalization program, which in turn coincided with the East Asian crisis and a series of corporate failures even in countries which were blamed on failures in governance systems. The impetus to reforming extant governance systems both in developed and developing countries came from the Cadbury Committee Report of 1992 which brought into focus the rule that corporate boards played in corporate governance. Governance initiatives in India since their formal initiation have come from the government via government legislations involving several amendments of the then Companies Act, 1956, which subsequently was replaced by the Companies Act, 2013, from the SEBI in the form of statutory regulations, and through other institutions such as the Institute of Chartered Accountants of India. The first round of reforms was initiated through the setting up of the Kumar Mangalam Birla Committee in 1999 by the SEBI, following the recommendations of which the SEBI introduced a separate section in the Listing Agreement of Stock Exchanges, namely, Clause

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49. The objectives of the Committee and the underlying purpose of the issuance of Clause 49 was the agency-theoretic view of corporate governance being deemed necessary for investor protection and raised standards of governance would enable the development of the domestic capital market, and through adopting globally accepted practices of governance, will ensure that investors in India are informed and protected as any investor in the best-developed capital markets of the world. Subsequent to the introduction and implementation of Clause 49, several more committees were set up to tighten up its different provisions in light of the experience on the ground, and also to clear up any ambiguity that crept into the provisions. The major committees that dealt with governance rules for listed companies were the Naresh Chandra Committee Report on Corporate Audit and Governance set up in 2002 by the Department of Company Affairs, Government of India, the Narayana Murthy Committee in 2003 constituted by the SEBI, the Companies Act 2013, replacing the Companies Act 1956, and the Uday Kotak Committee on Corporate Governance, 2017. Based on the recommendations of these various committees, corporate governance rules including those pertaining to the board of directors have been periodically revised in an attempt to be in step with market dynamics and other changes in the institutional environment. The bedrock of the Kumar Mangalam Committee recommendations and their implementation via Clause 49 was the regulations pertaining to the board of directors and were applicable to all listed private and public sector companies and had to be complied with in a phase-wise manner. While matters such as minimum board size, appointment and rotation of directors, limits on directorships, board procedures and responsibilities of board members have been laid down under the Companies Act 1956, regulations regarding board independence, board procedures, and financial disclosures, along with disclosures related to the composition and functioning of the directors were introduced for listed companies under the purview of the SEBI. In September 2015, SEBI issued the SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015 (LODR) with the aim to consolidate and streamline the provisions of existing listing agreements, and the provisions of Clause 49 were incorporated within the ambit of LODR 2015. Finally, in May 2018, SEBI issued the LODR (Amendment) Regulations which have sought to implement the key recommendations of the Uday Kotak Committee. Box 4.1 presents the timeline of corporate governance reforms in India since 1999.

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Box 4.1: Key Developments in Corporate Governance Reforms in India: 2000–2018 Date

Motivation/Rationale

1. Kumar Mangalam Birla Committee Report on Corporate Governance [2000] set up by to design a mandatory cum-recommendatory code for listed companies

– Corporate governance is considered an important instrument of investor protection particularly in light of the financial crisis in the Asian markets. – “Raising standards of corporate governance is “extremely relevant” to attract global capital. …would ensure that the Indian investors are in no way less informed and protected as compared to their counterparts in the best-developed capital markets and economies of the world.” – Provided a set of mandatory and non-mandatory requirements on board of directors, disclosure, investor protection and other aspects of company governance. Compliance by listed companies in three tranches (based on listing status and company size) spread over three consecutive years.

2. Institution of Clause 49 of the Listing Agreement [February 2000] by SEBI following the Birla Committee Report

– “With the opening up of the economy and to be in tune with the WTO requirements, if Indian companies have to survive and succeed amidst increasing competition from transnationals and foreign companies and it can only be through achieving ‘Excellence’ in their working.”

3. Department of Company Affairs (DCA)[2001–02]: Task Force on Corporate Excellence through Governance. Modified Companies Act, 1956 to incorporate provisions regarding Independent Directors and Audit Committees

– Triggered possibly by the Enron debacle and the Sarbanes Oxley Act of 2002 in the US, the Naresh Chandra Committee was entrusted to analyse and recommend changes, to the issues related to the statutory auditor-company relationship, certification of accounts and financial statements by the management and directors; and role of independent directors.

4. Naresh Chandra Committee Report on Corporate Audit and Governance [2002] appointed by DCA

– “Belief “of SEBI that “efforts to improve corporate governance standards in India must continue. This is because these standards themselves were evolving in keeping with market dynamics. Committee set up to evaluate the adequacy of existing corporate governance practices (Clause 49) and further improve these practices.” (continued)

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(continued) Date

Motivation/Rationale

5. Narayana Murthy Committee Report [2003]: Committee on Corporate Governance constituted by SEBI

– Important changes in Clause 49 related to the definition of independent directors, detailed outline of the role, responsibilities, and the powers of the audit committee, enhanced disclosure on accounting treatments, related party transactions and risk management as well as requirement of CEO/CFO certification of the accounts.

6. Revision of Clause 49 [October 2004] in light of the recommendations of the Narayana Murthy Committee Report

– More stringent requirements for board independence for companies with promoters (or persons related to promoters) as non-executive chairman.

7. Revision of Clause 49 [April 2008] as clarification and revision of Clause 49 (2004)

– Explanation of the expression “related to any promoter.”

8. Companies Act, 2013—Came into effect from August 30, 2013

– significant additions include the requirement of having at least one-woman director on board, expansion in the duties and responsibilities of directors, restrictions on number of multiple directorships, tenure and cooling period for independent directors, formation of audit committee for all registered companies, rotation, maximum tenure and cooling period of auditors, and mandated CSR spending for listed companies above a certain size.

9. Listing Obligations and Disclosure Requirements (LODR) Regulations—SEBI, September 2, 2015

– The LODR regulations put into effect all the provisions of the Companies Act, 2013 with respect to corporate governance. The Clause 49 requirements were subsumed into the much more expansive LODR regulations as listed above.

10. Uday Committee Report on Corporate Governance, October 5, 2017

– Recommendation to further tighten corporate governance standards related to size and board composition, CEO duality, women independent directors and host of other recommendations. (continued)

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(continued) Date

Motivation/Rationale

11. Listing Obligations and Disclosure Requirements (LODR) (Amendments) Regulations—SEBI, May 9, 2018

– Implementation by SEBI of many of the Uday Kotak Committee recommendations including the requirement to have at least one-woman independent director, separation of the position of CEO and Chairman, minimum board size of six, reduction in total number of directorships from eight to seven, higher quorum for board meetings. Implementation came into effect from April 1, 2019, for the top (500/1000) listed companies and scheduled to effective from April 1, 2020, for the top (1000/2000) listed companies.

Source Author’s compilation from various publicly available official documents

The corporate governance regulations issued from time to time by the SEBI starting from the Clause 49 regulations in 2000, have sought to cover the entire gamut of issues that one comes across in the literature regarding the board of directors. In particular, the regulations have contained provisions relating to (a) Composition of the Board, (b) Non-Executive Directors’ Compensation and Disclosures, (c) Other Provisions as to Board and Committees, which specify the frequency of meeting of the BOD and the number of multiple directorships that board members can hold in other companies, and (d) Code of Conduct for the Board members. A reading of the different committee reports and the provisions of the various corporate governance laws and regulations reveal that the provisions apply uniformly to all listed Indian companies, irrespective of whether these are group affiliates or not. The issue of minority shareholder expropriation in promoter-controlled firms was flagged for the first time in the Naresh Chandra Committee Report in 2002 whereby the committee stated that the controlling promoter of an Indian company can through several actions such as fixing the election of board members, packing boards with crony directors, to deprive minority shareholders of their de jure ownership rights without negatively affecting pre- or post-tax profits. The Uday Kotak Committee Report was even more scathing in its reference to promoter-controlled companies, whereby the report alludes to the “Raja” (Monarch) model of running an Indian company where promoter self-interest rules over the interests of the minority shareholders and other stakeholders.

4.5.3 Promoter Presence and Board Governance In view of the discussion in the preceding sub-section on regulations pertaining to the board of directors, this Section presents some key statistics on board characteristics of group affiliates. These board statistics relate to the composition of company boards

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in terms of the presence of independent directors, the presence of promoters in leadership positions signifying their control on the board, and finally the presence of women directors. For the purpose of analysis, since board variables are likely to be slow moving and change only marginally from year to year, for the sake of brevity of discussion, three time points are chosen. In particular, we select the year 2005 when the revised Clause 49 strengthening the definition of independent directors came into effect (Box 4.2), the year 2013 marking the enactment of the new Companies Act, 2013, and the year 2018, the end date of the study period and five years post the new Act. The time points chosen can provide some insight into how keyboard characteristics that are relevant for evaluating the governance by company boards have evolved in response to the various changes in board regulations. For these three time points, the results of the analysis of board characteristics are presented in Table 4.7 which is organized in terms of four panels, Panel A to Panel D. Box 4.2: Changes in Board Composition and Independence: 2000–2014 Board composition

Board Composition

October 2004 February 2000 “Optimum combination of executive Similar as February, 2000 and non-executive directors with not less than fifty percent of the board of directors comprising of non-executive directors. The number of independent directors would depend on whether the Chairmanisexecutiveornon-executive. In case of a non-executive chairman, at least one-third of board shouldcompriseofindependent directors and in case of an executive chairman, at least half of board should comprise of independent directors

Board Composition

Board Composition

April 2008 Additional qualification for boards with non-executive chairman If the non-executive Chairman is a promoter or is related to promoters or persons occupying management positions at the board level or at one level below the board, at least one-half of the board of the company should consist of independent directors

October 2014 Additional qualification: (a) The Board of Directors of the company shal lhave an optimum combination of executive and non-executive directors with at least one-woman director (b) Companies Act, 013 Section 149(1) requires at least one women director for not only for listed companies but also, for such non listed companies as prescribed (continued)

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(continued) Board composition

Board Composition

Board Composition

Board Composition

Determination of Independence “Independent directors” means directors who apart from receiving director’s remuneration, do not have any other material pecuniary relationship or transactions with the company, its promoters,itsmanagementorits subsidiaries, which in judgment of the boardmay affect independence of judgment of the director

Determination of Independence Revised “Independent directors” shall mean a non- executive director of the company who a. apart from receiving director’s remuneration, does not have any material pecuniary relationships or transactions with the company, its promoters, its directors, its senior management, or its holding company,its subsidiaries and associates which may affect independence of the director; b. is not related to promoters or persons occupying management positions at the board level or at one level below the board; c. has not been an executive of the company in the immediately preceding three financial years; d. is not a partner or an executive or was not partner or an executive during the preceding three years, of any of the following: (i) the statutory audit firm or the internal audit firm that is (ii) associated with the company, and (iii) the legal firm(s) and consulting firm(s) that have a material association with the company e. is not a material supplier, service provider or customer or a lessor or lessee of the company, which may affect independence of the director; and f. is not a substantial shareholder of the company, i.e., owning two percent or more of the block of voting shares

Determination of Independence Similar as October 2004

Determination of Independence Similar as October 2004

Source Author’s compilation from various publicly available official documents

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Table 4.7 Board Characteristics of Indian Group Affiliates: 2005–2018 2005 A. Board Size

2013

2018

10.02 9.54

8.42

B. Promoter Control of Board (proportion of affiliates) 1.Promoter present on board

0.66

0.84

0.50

2. No control (promoter not CEO or Chairperson)

0.38

0.22

0.54

3.Operational Control (promoter CEO but not Chairperson)

0.06

0.07

0.04

4.Strategic Control (promoter not CEO but Chairperson)

0.14

0.24

0.15

5.Full control (CEO duality—promoter both CEO and Chairperson)

0.42

0.46

0.26

C. Board Independence Percentage of independent directors

46.51 52.53 53.46

Percentage of independent directors with executive chairperson

52.49 53.69 53.81

Percentage of independent directors with non-executive chairperson

42.68 51.77 52.53

Percentage of independent directors with non-executive chairperson who 41.68 51.76 52.39 is promoter Percentage of Independent Directors under no control

43.60 51.31 53.65

Percentage of Independent Directors under operational control

41.26 49.83 52.59

Percentage of Independent Directors under strategic control

45.20 53.16 52.72

Percentage of Independent Directors under full control

50.38 53.22 53.66

D. Female director presence on Board (proportion of companies in which at least one female director is present) Female director present on board

34.54 35.92 61.96

Female executive director present on board

8.75

10.96 6.37

Female independent director present on board

10.57 16.19 39.07

Female grey director present on board

15.22 9.77

16.52

Total number of companies in sample

388

581

593

Source Author’s computation based on Prowess Database

As can be seen from Panel A which presents estimates of average board size across group affiliates, average board size of group affiliates has declined from around 10.02 directors per board in 2005 to 8.42 directors per board in 2018. Estimates from an earlier period, between 2003 and 2008, point to a declining trend in board size. The estimates for the later period presented in Table 4.7 seem to be consistent with the trend found for the earlier years since Clause 49 came into effect. The decline in board size could reflect the efforts on the part of companies to meet the gradually tightening up of the board independence requirement through reducing the board size rather than by increasing the number of independent directors. Panel B of Table 4.7 presents estimates of promoter control of board as captured by the proportion of group affiliates in each of the three years under different types of promoter control. As different estimates of promoter ownership in Sect. 4.4 show,

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promoters of group affiliated firms have persistently held controlling voting blocks in group affiliates, having on an average a majority share in group affiliates. From these estimates, although it is presumed that voting control would give promoters management control, the incidence of this cannot be deduced from the equity shareholding. Using board level data, such estimates have been derived in Table 4.7. To capture the range of promoter control in management, following Luo and Chung (2013), the sample of group affiliates is classified by patterns of family control as follows (1) no promoter control, where neither the chairperson nor the CEO is a promoter, so the firm is under professional management (2) operational control, where the chairperson is a non-promoter but the CEO is a promoter (3) strategic control, where the chairperson is a promoter but the CEO is a non-promoter, and finally (4) full control or CEO duality where the promoter is both the chairperson and CEO. As is evident from the Table, notwithstanding the pervasiveness of controlling stakes of promoter ownership in group affiliates (Sect. 4.4), not all such firms have promoters on their boards; in 2005, the proportion of firms with at least one promoter present on board was 66%. However, what is interesting is to see that while promoter consolidation in terms of voting share has taken place over time, professionalization of group affiliated companies seems to have happened; the proportion of companies with no promoters on board in leadership positions has seen an increase with more than half of the sample firms having promoters as either a CEO or as a chairperson. This is also consistent with the decline seen between the two time points 2005 and 2018 in the proportion of companies in which a promoter was present. The other interesting point to note from the estimates in Panel B is that of firms where promoters were present on board, instances of a promoter being a CEO but not a chairperson are relatively rare; only 6% of companies in 2005, 7% in 2013 and 4% in 2018 of firms had operational control by the promoter. Affiliates with promoters as chairperson but not as a CEO implies that promoters in such companies are entrusted more with providing a strategic vision for the company, whereas the day-to-day management is professionalized. As of 2018, 15% of companies are in this category, a category that has been mandated to have at least 50% independent directors as per the rules introduced in 2008. Finally, it is evident from the estimates of CEO duality that the incidence of promoters in dual positions in group affiliates, although substantial has shown a noticeable decline in 2018 over earlier levels and this decline is consistent with the overall trend toward professionalization of boards apparent in group companies.

4.5.4 Board Independence A typical board of modern corporations consists of inside or executive directors who are full time employees of the company and are involved in its day-to-day operations and non-executive or outside directors who do not have any executive responsibilities and play mostly an advisory role. The outside directors can be further classified

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as “affiliated directors” (or grey directors) and “non-affiliated directors.” Affiliated directors are former company officers, relatives of the company officers, or those who have existing business relationships with the company such as investment bankers and lawyers. Non-affiliated directors are outside directors with no such affiliation. It is the non-affiliated outside directors, commonly referred to as “non-executive independent directors” or simply as “independent directors” who are envisaged to perform the monitoring role and are widely regarded as the fiduciaries of shareholder interests. From an agency-theoretic premise, one of the important focuses of corporate governance regulations across countries is to institute an optimal presence of independent directors on the board in order to increase the efficacy of board monitoring. It is argued that if boards exist to monitor shirking or self-dealing by inside management, then outside directors in general, and independent directors, in particular, should be more effective monitors than insiders whose interests may not be aligned with that of outside shareholders (Weisbach 1988). Independent directors, keen to protect their reputational capital and to avoid being sued by shareholders, have incentives to promote the interests of shareholders and be effective monitors (Bhagat et al. 1987; Fama 1980). Further, from a resource dependency perspective, outside busy directors, through their interlocks with other companies, can generate benefits by helping to bring in needed resources, suppliers, and customers to a company (Pfeffer 1972). Board independence worldwide has typically been defined objectively based on objective criteria requiring either the presence of a minimum number or a minimum proportion of independent directors. However, this is only part of the exercise of constituting an independent board as it is necessary to first identify directors who are “independent” of inside management so that there is no conflict of interest in monitoring the management. The usual way of defining “independent” directors in most regulations is to first state that an independent director is one for whom any material relation with the company is absent, and then identify conditions that prima facie suggest that material relations could be present. Any person who does not fall under these conditions is then deemed to be independent. The law in various countries differs according to (i) the list of the presumptive conditions that lead to a material relation and hence lack of independence and (ii) the authority which makes this determination. In India, both the composition of the board as well as the definition of independence have been revised from time to time based both on committee recommendations and experience on the ground. Changes have been made with the singular objective of strengthening board independence in line with existing best practices. Further, attempts have been made to bring about greater congruence between the legislations/ regulations issued by different administrative authorities, in terms of what constitutes an independent board, and who constitutes and independent director. Box 4.2 presents the evolution of policies with respect to board composition and independence since 2000.

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As is evident from the different regulations on board composition and the definition of director independence, there has been a concerted attempt at strengthening board independence. At the same time, there is a clear recognition that board dynamics depend on whether the chairman of the board is a non-executive director, in which case, the board independence requirement is lower than when the chairman is an executive director. Further, over time, there has been an increasing recognition that given the pervasiveness of promoter control and the potential agency costs associated with it, the “concession” that was built in the initial regulation of the requirement of independence of a board where the chairman is a non-executive is likely to be disturbed when the non-executive is a promoter of the company. By requiring that at least half of the board should comprise independent directors when the chairman is an executive or when the chairman is a promoter, the regulation is recognizing that a promoter in a leadership position without being an executive, can exert excessive control in the operation of the company. As with the strengthening of regulations with regard to board independence, Box 4.2 also reveals the move toward achieving greater objectivity in the definition of director independence. The original definition of what construes as independence of a director was kept broad perhaps for the sake of pragmatism and flexibility, but as the Naresh Chandra Committee recognized, such a definition is circular and tautological. Further, with promoter control of companies so pervasive, the application of such a definition by any promoter in a leadership position to select independent directors, could lead to the constitution of friendly boards rendering monitoring by independent directors weak. The revised definition of independence since October 2004 seeks to incorporate a set of bright line tests for independent directors that are in line with international best practices. Turning toward an evaluation of board independence in group affiliated firms, items 1–4 of Panel C of Table 4.7 present estimates of board independence according to the regulations presented in Box 4.2, and items 5–8 of Panel C present comparative estimates for different types of promoter control as specified under items 2–5 of Panel B. Several observations can be made from these estimates, especially with regard to compliance of affiliates to changes in regulations pertaining to board independence. As can be seen from the timeline of changes in the regulations pertaining to board composition and independence, requirement of a minimum percentage of independent directors to be appointed to the board of a listed company has been conditional on whether the chairperson is an executive or a non-executive director. The regulation that existed between 2004–2008, did not consider the possibility that a chairperson who is designated as an non-executive can de facto act as an executive director if the person is a promoter of the firm, in which case the management should require the same extent of independent oversight had the chairperson been an executive director. This lacuna was removed in the revised provisions in 2008 which specified that the presence of independent directors for companies with a promoter chairperson should be the same as for companies with an executive chairperson. Panel C of Table 4.7 presents estimates pertaining to board independence of firms with different extents of promoter control when promoters are in leadership positions. Here too, there is little

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variation in board composition in 2013 and 2018, the level remaining almost the same since 2011 (not reported). This seems to coincide with the time when average equity holdings of promoters crossed the majority mark and could be indicative of the fact that there is no discriminating power left in using the extent of board independence as a marker for inferring about firm governance. As is evident item 1 of Panel C, the percentage of independent directors in group affiliates in 2005 was 46.51%. This estimate is arrived at by pooling all affiliates, those for which the mandatory requirement is one-third (chairperson is a non-executive) and those with executive chairperson for which the requirement of independence is at least 50%. By 2013 (earlier estimates not reported), the percentage of independent directors irrespective of whether the director is executive/non-executive or promoter, has crossed 50% on an average, and was 53.46% in 2018, suggesting that at least some firms, including perhaps those with a non-executive, non-promoter chairperson, over complying. Item 2 of Panel C captures the percentage of independent directors for affiliates with executive chairperson, for which the minimum requirement of such directors on board is 50%. It is clear from the estimates that on average such companies are complying with the regulation. Turning to item 3 of Panel C, the estimates pertain to that class of group affiliates with non-executive chairperson, the minimum requirement for which was one-third of the board. This category is relevant for the period 2005–08, and 2005 estimates again suggest over compliance with the regulatory requirement on an average. While it appears from the estimate of year 2005 that the extent of over compliance remained below 50%—the level that is required for companies with executive chairperson -, estimates for later years, 2013 and 2018, indicate that even for these group of companies, the percentage of independent directors crossed the 50% cut-off. Thus, tying independence requirements to the specific position of the chairperson has not made a difference on the ground. Finally, the estimates of board independence under item 3 of Panel C capture compliance with the revised regulation in 2008 of requiring boards with non-executive chairperson who is a promoter, to constitute boards with at least 50% directors. The percentage of group affiliates that fall under this category in the sample as of 2005 was 25.1% for which the independence requirement would be 50%. Estimates for 2013 and 2018 suggest that these set of firms have complied with the higher independence requirement.

4.5.5 Women Directors on Board As in most countries, women are under-represented on the board of directors of companies.11 India has been no exception in this regard, with women, on an average, accounting for less than 5% of board seats in listed Indian non-financial companies between 2005 and 2014 (Sarkar and Selarka 2021). Since 2003, beginning with the 11

A survey of 8,600 companies in 49 countries found that women held only 16.9% of all global board seats as of 2018. Catalyst, Quick Take: Women on Corporate Boards (March 13, 2020).https:// www.catalyst.org/research/women-on-corporate-boards/ accessed on July 17, 2020.

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institution of gender quotas in Norway, there has been a push toward greater gender diversity on corporate boards over the years has been primarily driven by the business case for having more women on company boards.12 In India, in order to increase the presence of woman directors on company boards, legislation was enacted in 2013 with to institute gender quotas on company boards under section 149(1) of the Companies Act, 2013 (MCA, 2013), which required every company or classes of companies, as may be prescribed, to appoint at least one-woman director.13 Initially, similar to other countries, the law in India did not specify the type of woman director, namely, grey or independent, to be appointed under the quota requirement. However, a more stringent gender quota was introduced by the SEBI under the Listing Obligations and Disclosure Requirements (LODR) (Amendment) Regulations 2018 which required the top 1000 listed companies in India to have at least one independent woman director by April 1, 2020.14 Panel D of Table 4.7 presents estimates of the proportion of group affiliates with at least one-woman director, and corresponding estimates for women executive, independent, and grey directors for three time points 2005, 2013, and 2018. Additionally, Fig. 4.8 plots trends in the presence of women director on company boards in terms of the percentage of affiliates with at least, one-woman director (dfdir), one independent director (dfind), one grey director (dfgrey) and one executive director (dfed). Till the year 2018, both the Indian law and correspondingly the SEBI regulations did not specify the type of woman director, namely, grey, or independent, to be appointed to meet the quota requirement. However, one of the channels through which family control is exerted on the board of family firms, a large majority of which are group affiliates is through the presence of grey directors, directors who are non-executive, but who, unlike the independent directors, are often founding family members or are their relatives. Thus, compliance of the gender quota for group firms could be a channel through which family control of the board can simultaneously be increased. As is evident from the estimates provided in Fig. 4.8 and Table 4.7, there is a clear structural break in the percentage of companies with at least one-woman director, and a steep increase in the percentage of dfdir shows increasing compliance with the relevant law. Significantly, there does not seem to have been any jump 12

More inclusive and diverse boards, it is argued, are likely to be better at decision making and monitoring as directors drawn from different demographics are in a better position to understand customers and stakeholders, bring in fresh perspectives, new ideas, different problem solving, advisory and monitoring attributes, and have a wide range of experiences that helps them deal with issues in a more holistic way, all of which are likely to have a positive effect on a company’s bottom line (Davies Report; Ferreira, 2011; Anderson et al., 2011). 13 The rules with respect to the implementation of this Sub-section 149(1) were notified on March 31, 2014 and required that all listed companies, as well as all unlisted registered companies with a paid-up share capital of Rs. 100 crore or more, or turnover of Rs. 300 crore or more, have to appoint at least one woman on their board within six months of the notification. 14 The timeline for the implementation of the new regulation would be as follows: the top 500 listed entities shall have at least one independent woman director by April 1, 2019, and the Board of directors of the top 1000 listed entities shall have at least one independent woman director by April 1, 2020.

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70 60 50 40 30 20 10 0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 dfdir

dfed

dfind

dfgrey

Fig. 4.8 Group affiliates with at least one woman director (%): 2005–18. Source Author’s computation from Prowess database

as of 2018 in the appointment of grey women directors in group affiliates since the enactment of the quota, and instead the compliance is being driven by the appointment of women independent directors. This trend could be further strengthened given the revised provision for independent boards for listed companies under the LODR (Amendments) Regulations of SEBI, as mentioned above.

4.6 Concluding Comments This chapter analyzes the ownership and governance of Indian business groups in the backdrop of evolving laws and regulations in India. The analysis is conducted using a panel data of group affiliated and unaffiliated firms for the period 2005–2018 during which the governance reforms that were initiated in the earlier years took root, and several new ones were introduced through revisions of existing regulations and laws. The twin objectives of the analysis have been to examine (i) whether the nature of the agency problems pertinent to business groups as manifested in their ownership and control structures have fundamentally changed in response to dynamic changes in their institutional environment, and (ii) whether reforms introduced to change the ways in which groups are governed by the board of directors have made any impact on the way these groups are actually governed. The analytical approach has been to understand the changes, if any, through the lens of history, to find out whether there is path dependence in the present functioning of the groups, and whether de jure

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changes in governance mechanisms that have been introduced progressively through board reforms has de facto altered the governance structure of business groups in line with the intended objectives. Contrary to expectations drawn from the institutionalist perspective that the relevance of business groups that fill institutional voids will wane as markets develop, the analysis in this chapter points to the continued predominance and persistence of Indian business groups in corporate sector activity. Several of the groups, like Tata and Birla, which were established in the pre-independence era, have continued to remain in leadership position with only a handful of large business groups continuing to dominate corporate sector activity irrespective of the changes in the institutional environment. Big groups have become even bigger in terms of their asset base, and changes in the relative positions of groups at the top end of the distribution have been sticky at best even after more than a hundred years of their existence and the entry of new groups from time to time. Within groups, ownership structures have become more concentrated over time, with promoters of almost of all groups now having majority control in all the listed firms of the groups. The pervasiveness, persistence, and dominance of promoters in Indian business imply that there is little scope of monitoring internal management by other large blockholders. Hence a disproportionate burden of governance has to fall on the board of directors of group companies. This is perhaps why the major governance reforms in India since their initiation in early 2000s have focused on good board governance. Thus, regulations have emphasized board independence of listed companies as reflected in the requirement of the percentage of independent directors and the definition of independence. Presumably, while agency problems of business groups have stayed the same or even aggravated, board regulations have exhibited the dynamism to address the potential agency costs. Data on observed board characteristics do suggest that these regulations are influencing board structure of affiliated firms in directions intended by the regulations. In some cases, the data suggests that there has been over compliance. Thus, with regard to the main question of whether de jure reforms with regard to board governance have translated to intended de facto changes in observable “good” governance parameters, the answer is in the affirmative. However, whether this is on account of simply tick box compliance or whether there are fundamental ways in which governance of groups is changing and resulting in lower agency costs, remains to be seen.

Annexure See Table A.1.

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Table A.1 Data on Indian business groups: an analysis of the prowess database 2018 A. Business Groups with both listed and unlisted firms

Number of firms

Total Number of Distinct Business Groups Reported in the Database

734

11,802

Total Number of Distinct Business Groups Reported in the Database with number of firms per group reported > = 2

703

11,771

Total Number of Distinct Business Groups Identified in the Database with number of firms per group reported > = 2 AND with firm level data on total assets

569

5086

Total Number of Distinct Business Groups Reported in the Database with at least one listed 659 firm

2094

Total Number of Distinct Business Groups Reported in the Database with at least one listed 534 firm AND firm level data on total assets

1277

B. Groups with at least one listed firm

C. Groups with at least one unlisted firm Total Number of Distinct Business Groups Reported in the Database with at least one unlisted firm

663

9708

Total Number of Distinct Business Groups Reported in the Database with at least one unlisted firm AND firm level data on total assets

417

3823

157

245

44

191

D. Groups with only listed firms Total Number of Distinct Business Groups Reported in the Database with only listed firms AND firm level data on total assets E. Groups with only unlisted firms Total Number of Distinct Business Groups Reported in the Database with only listed firms AND firm level data on total assets Source Author’s computation based on Prowess Database

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Demsetz H (1983) The structure of ownership and the theory of the firm. J Law Econ 26(2):375–390 Dodd P, Warner JB (1983) On corporate governance: a study of proxy contests. J Financ Econ 11(1–4):401–438 Douma S, George R, Kabir R (2006) Foreign and domestic ownership, business groups, and firm performance: evidence from a large emerging market. Strateg Manag J 27(7):637–657 Dutta S (1997) Family business in India. Response Books, New Delhi Encarnation DJ, Mason M (1990) Neither MITI nor America: the political economy of capital liberalization in Japan. Int Organ 44(1):25–54 Faccio M, Lang LH (2002) The ultimate ownership of Western European corporations. J Financ Econ 65(3):365–395 Fama EF (1980) Agency problems and the theory of the firm. J Polit Econ 88(2):288–307 Fama EF, Jensen MC (1983) Separation of ownership and control. J Law Econ 26(2):301–325 Ferris SP, Jagannathan M, Pritchard AC (2003) Too busy to mind the business? Monitoring by directors with multiple board appointments. The J of Finance 58(3):1087–1111 Finkelstein S (1992) Power in top management teams: dimensions, measurement, and validation. Acad Manag J 35(3):505–538 Gilson RJ (2006) Controlling shareholders and corporate governance: complicating the comparative taxonomy. Harvard Law Rev, 1641–1679 Goswami O (1989) Sahibs, babus, and banias: changes in industrial control in eastern India, 1918– 50. J Asian Stud 48(2):289–309 Goswami O (2000) The tide rises gradually corporate governance in India, Draft for Presentation at the Informal Workshop, OECD. http://www.OECD.org/dataOECD/6/47/1931364.pdf Granovetter M (1995) Coase revisited: business groups in the modern economy. Ind Corp Chang 4(1):93–130 Hazari RK (1966) The corporate private sector: concentration ownership and control. Asia Publishing House Jensen MC, Meckling WH (1976) Theory of the firm: managerial behavior, agency costs and ownership structure. J Financ Econ 3(4):305–360 Johnson S, La Porta R, Lopez-de-Silanes F, Shleifer A (2000) Tunneling. Amer Econ Rev 90(2):22– 27 Kali R, Sarkar J (2011) Diversification and tunneling: evidence from Indian business groups. J Comp Econ 39(3):349–367 Khanna T, Palepu K (2000) Is group affiliation profitable in emerging markets? an analysis of diversified indian business groups. J Financ 55(2):867–891 Khanna T, Palepu K (2005) The evolution of concentrated ownership in India: broad patterns and a history of the Indian software industry. In: A history of corporate governance around the world: Family business groups to professional managers, pp 283–324. University of Chicago Press Khanna T, Yafeh Y (2007) Business groups in emerging markets: Paragons or parasites? J Econliterature 45(2):331–372 Khanna VS (2005) The economic history of organizational entities in ancient India. Michigan Law Econ Res Paper, 5–14 Kumar J (2008) Econometric analysis of corporate governance in India: firm performance and dividend policy in India, VDM Verlag Porta RL, Lopez-de-Silanes F, Shleifer A, Vishny RW (1998) Law and finance. J Polit Econ 106(6):1113–1155 La Porta R, Lopez-de-Silanes F, Shleifer A (1999) Corporate ownership around the world. J Financ 54(2):471–517 Leff N (1976) Capital markets in the less developed countries: the group principle. Money Financ Econ Growth Dev 3(1):97–126 Luo XR, Chung CN (2013) Filling or abusing the institutional void? Ownership and management control of public family businesses in an emerging market. Organ Sci 24(2):591–613 Masulis RW, Pham PK, Zein J (2011) Family business groups around the world: financing advantages, control motivations, and organizational choices. Rev Financ Studies 24(11):3556–3600

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Maury B (2006) Family ownership and firm performance: empirical evidence from Western European corporations. J Corp Finan 12(2):321–341 Mehta MM (1955) Structure of Indian Industries: A Statistical Study in the Size, Location, and Integration of Industrial Units in the Seven Selected Industries of India, Viz., Cotton, Jute, Sugar, Iron and Steel, Coal, Paper, and Cement. Popular book depot Morck R, Yeung B (2004) Family control and the rent–seeking society. Entrep Theory Pract 28(4):391–409 NCAER (1959) The managing agency system, national council of applied economic research, New Delhi, Publishers Ouchi WG (1980) Markets, Bureaucracies, and Clans. Adm Sci Q 25(1):129–141 Pfeffer J (1972) Interorganizational influence and managerial attitudes. Acad Manag J 15(3):317– 330 Pound J (1988) Proxy contests and the efficiency of shareholder oversight. J Financ Econ 20:237–265 Ramaswamy K, Li M, Petitt BS (2012) Why do business groups continue to matter? A study of market failure and performance among Indian manufacturers. Asia Pacific J Manag 29(3):643– 658 Roe M (2004) The institutions of corporate governance. Discussion Paper No. 488, Harvard Law School Sarkar, J, Selarka E (2021) Women on board and performance of family firms: Evidence from India (with Ekta Selarka), Emerging Markets Review, Elsevier, Volume 46, March 2021, 100770.https://doi.org/10.1016/j.ememar.2020.100770 Sarkar J, Sarkar S (2000) Large shareholder activism in corporate governance in developing countries: evidence from India. Int Rev Financ 1(3):161–194 Sarkar J, Sarkar S (2009) Multiple board appointments and firm performance in emerging economies: evidence from India. Pacific-Basin Finance J 17(2):271–293 Sarkar J (2010) Business groups in India. In: Colpan, Asli M, Hikino, Takashi L, James R (Eds) The Oxford handbook of business groups. Oxford University Press: New York. Sarkar J, Sarkar S (2012) Corporate governance in India. SAGE Publishing India SEBI (2003) Recommendations of the narayana murthy committee on the revised clause 49 http:// www.sebi.gov.in/Index.jsp?contentDisp=Section&secid=5 Shleifer A, Vishny RW (1997) A survey of corporate governance. J Financ 52(2):737–783 Tripathi D (2004) The Oxford history of Indian business. Oxford University Press, New Delhi Weisbach MS (1988) Outside directors and CEO turnover. J Financ Econ 20:431–460

Chapter 5

The Multi-entity Structure and Control in Business Groups Surajit Mazumdar

Abstract The literature on business groups in “emerging” markets emphasizes several dimensions along which the group form may differ from its presumed opposite—the stand-alone firm. However, what does not usually capture too much attention is that the business group structure in India can and does incorporate several companies/firms which are neither publicly listed nor even individually large. So much so that several apparently stand-alone companies can also be parts of networks connecting them to other such companies/firms. The inter-connections which link these several entities are, however, crucial inter alia to the exercise of control by business families over capital and wealth far in excess of what is legally owned by them. Concentrated control over assets and concentrated “ownership” of companies are the related outcomes of these and this provides an important reason for the resilience of the multi-entity group structure. The specific structure of the network of individual business groups and their participating entities, however, change over time in response to changing institutional contexts as well as due to its endogenous dynamics. This paper seeks to develop these propositions using the specific case of the Reliance group as an illustration and further argue that liberalization, instead of developing a “market for corporate control,” has only served to reinforce this method of “entrenchment.”

5.1 Introduction The Indian business group is a sub-species of the larger category of entities which share the common characteristic of being different from the classic stand-alone firm. Such groups, which are said to be common in “emerging market” contexts, however, have been distinguished from their supposed opposites along several dimensions rather than one. And these do not even necessarily imply each other. A multi-company structure, conglomerate diversification patterns, and the role played within them by S. Mazumdar (B) Centre for Economic Studies and Planning, Jawaharlal Nehru University, New Delhi, India e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_5

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large family networks are some of the typical distinctive characteristics of groups referred to in the literature (Leff 1978, Amsden and Hikino 1994, Granovetter 1995, Ghemawat and Khanna 1998, Guillen 2000, Khanna and Palepu 2007, Khanna and Yafeh 2007). Even after this there are questions about whether the group is a specific form of the firm or is it a structure of coordination between firms. Contrast for instance “The group is a multi-company firm which transacts in different markets but which does so under common entrepreneurial and financial control” (Leff 1978, p 663) with the notion of the group as a “hybrid organizational form between the firm and the market” (Khanna and Yafeh 2007, p. 333). When looked at from the standard corporate governance perspective, it is not merely their multi-company structure but the inter-connectedness of legally independent publicly listed companies and their concentrated ownership that has been emphasized. Thus, except in a purely negative sense, there is no one clear definition of what constitutes an emerging market business group. The recognition and study of business groups as a feature of the structure of the Indian private corporate sector, however, first emerged from a very different concern, namely, the “concentration of economic power” or the “monopoly problem” (Government of India 1964, 1965; Hazari 1966; Namjoshi 1966). The central focus here was on the control over a large proportion of assets, particularly in the industrial sector, by a relatively small number of business families. Relevant to assessing the degree of such concentration was the significance of what several early studies had noted and amassed considerable evidence on, namely, inter-connections between legally independent companies or the phenomenon of what was termed “industrial combination” (Mehta 1952, Basu 1958, Nigam 1959, Nigam and Chaudhuri 1960, Mohnot 1962, Nigam and Joshi 1963, Joshi 1965, Kothari 1967). Ultimately this led to a specific conceptualization of the group as a single and cohesive decision-making entity that incorporated within itself several legally separate units. “A corporate group may be defined as consisting of units which are subject to the decisionmaking power of a common authority… The group functions as a single organisation, nevertheless, though each of the corporate units under its control is a separate legal entity” (Hazari 1966, p. 5).

The Monopolies Inquiry Commission (Government of India 1965) and the Industrial Licensing Policy Inquiry Committee (Government of India 1969) worked with the same understanding of the group. The latter described big groups as “Large Industrial Houses,” and in addition drew attention to the presence of “Large Independent Companies”—big firms that had not assumed the group form. Two important aspects of the Indian business group so defined were the emphasis on concentrated control over assets rather than in their legal ownership and that the group could include several units of diverse sizes as well as forms—and these included not merely publicly listed companies but also partnership and proprietorship firms, trusts and private companies. The first of these meant that no presumption was made to the effect that separation of ownership and control of capital was necessarily absent or limited in the Indian business group. Correspondingly, the pooling of capital owned by associated individuals linked to each other through large family networks was also not deemed

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to be an essential feature of the business group. On the contrary, the mechanisms by which centralized control was exercised, over assets not only dispersed across different corporate units but also not necessarily owned by the controlling family, was itself an object of investigation. This, in fact, was one reason among others why it was important to acknowledge and examine the significance of the second feature, that the group structure included entities other than listed public companies.

5.2 The Business Group as a Dynamic Structure Corporate units and groups are of course creations of human agents. Implicit in the conception of a centralized control over several legally separate units is the likelihood that their creation and their integration into a whole are also the deliberate creation of that controlling authority. Just as there can be a variety among single companies in terms of size, levels, and kinds of diversification and internal organization, and each one can change over time in terms of all these dimensions by a process in which its management is an active agent, so too in the case of business groups. This can include variations in the number and types of different units and the structure integrating them as a whole—in short, the architecture of the group.1 Not only is the guiding hand of the central controlling authority behind the group structure, even the recourse to the group form is deliberate. Indeed, single units can also evolve into groups— several groups recognized as such later, like Godrej, can in fact be traced back to the “Large Independent Companies” of the 1960s. When controlling authorities are families, centralized control can also facilitate “restructuring” of groups to manage generational transitions or to give effect to family divisions. This mobility in the group structure means that they are not amenable to be defined in extremely narrow and rigid terms. The history of the Reliance “group” from its beginnings in 1958 provides an illustration of the dynamic character of business groups (Mazumdar 2006). Almost instinctively, in any study Reliance would generally be considered a representative of the category of business groups. Reliance Industries thus would typically be always treated as a group affiliated company rather than a stand-alone one. Yet, as its history briefly recounted below will indicate, Reliance in several phases of its history would not fit one or the other of several standard conceptions of the “emerging market” business group and almost never all of them. The Reliance group began its history in trading conducted initially through a partnership firm, Reliance Commercial Corporation. It was only in 1966 that it also entered manufacturing along with the incorporation of the first joint-stock company of the group, Reliance Textiles and Engineers Ltd. In the next decade, five more 1

For instance, among the 75 groups with assets more than Rs. 5 crores (50 million) in 1964 identified by the MIC, the total number of group companies ranged from a mere 4 or 5 in some cases to as many as 151 in the case of the Birla group. In the case of the Birla group, less than 8% of its total assets were accounted for by the largest company in the group, but there were also many groups where a single company accounted for over 90% of the total group assets.

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companies were created —Reliance Exports in 1969; Vimal Fabrics in 1973; and in 1975 Anil Fabrics, Dipti Textile Industries, and Nina Textile Industries were incorporated to take over the businesses of existing partnership firms. However, till 1977 none of the 6 companies was listed on any stock exchange—instead, they were all narrowly held private limited companies. Nevertheless, through a debt-financed growth, the group had assumed some size and Reliance Textiles had to register itself under the then-prevailing Monopolies and Restrictive Trade Practices Act in 1978. The manufacturing activity of the group during this initial phase, spread across four companies, was concentrated in the knitting and weaving of synthetic fabrics and processing of yarn and gray fabrics. Though with some addition of new activities and the acquisition of another company (Sidhpur Mills), the textiles phase of the group continued till 1982. After that the growth for a decade came to be increasingly centered on polyester and other petrochemicals. This growth carried Reliance to the very top of India’s corporate hierarchy by the end of the decade of the 1980s. While there was a rapid proliferation in the number of companies alongside this (Table 5.1), all the manufacturing activity came to be concentrated in what was for several years the only publicly listed company in the group and was ultimately rechristened as Reliance Industries Ltd. The first listing of a Reliance group company was preceded by the amalgamation of Reliance Textiles into another company, Mynylon Ltd., which was doing no business at that time. The amalgamation was followed by a change in the company’s name, and city of registration, to those of the acquired entity. This apparently odd rebirth of Reliance Textiles considerably increased the number of shares held by its controlling family from which a part was divested to the public to get the company listed. Subsequently, as the company repeatedly and successfully tapped the capital market for funds in the 1980s, the share capital and the number of shareholders multiplied. The family retained its control over the company through a stake that was increasingly held not by individuals but by other companies, the many which were added to the stable during this period. Table 5.1 Increase in the number of companies of the Reliance group, 1978 to 1989 Year- >

1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

6 Companies Registered in the Year

7

2

10

17

21

31

6

49

5

2

5

Cumulative 12 total of group companies

19

21

31

48

69

100

106

155

160

162

167

Note The above table excludes companies for whom the relevant information was not available. Seven companies that were registered earlier but acquired during this period have also not been included Source Mazumdar (2006)

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With the advent of liberalization, Reliance expanded its petrochemical operations and moved into oil and gas, power, telecom as well as several other new services activities. Manufacturing operations, however, continued to be concentrated in one public company and its subsidiaries. Even when new companies were created to start a business or companies were acquired, they were eventually merged into Reliance Industries. This merger process began with Sidhpur Mills in 1982, which was followed by that of Reliance Petrochemicals in 1992, Reliance Polypropylene and Reliance Polyethylene in 1995, Reliance Petroleum in 2002, the privatized IPCL in 2007, and then another Reliance Petroleum in 2009. In the meanwhile, in 2005 the two Ambani brothers also split up the group among themselves which also narrowed the business spread of each. While the two factions have had 10 odd companies listed on stock exchanges, most of them were part of the Reliance ADAG (Anil Ambani) that was engaged in mainly power, telecom, and other services. The Reliance Industries group (Mukesh Ambani), in which the oil and gas and manufacturing operations came to be concentrated, eventually ended up with only two listed companies even as it diversified into retail and telecom. Reliance Industries, however, continued to be controlled by the family through the shareholding held by several other companies and one trust, and LLPs after the Limited Liability Partnership Act, 2008 came into force. It in turn became the sole “promoter” of the other listed company (holding 45% of its share capital as on March 2017). Thus, the simultaneous control of a family over several legally separate units has been a feature of Reliance’s structure through most of its history, at least for the last four and a half decades. For some period, this was a feature without there being any publicly listed company in the group’s stable. It became one of India’s largest groups with a single listed company. No tendency toward conglomerate diversification characterized its initial journey to that position—if it exhibited any tendency toward conglomerate diversification that was later. Like almost all other groups, it also experienced a family division. So, when, if ever, has Reliance been a business group? The answer will change depending on the specific definition one adopts. By the original Hazari conception, however, it has been almost throughout a business group, but its structure has evolved and altered over time—perhaps, one may say, as a response to its own growth and the changing environment of its operation.

5.3 The Business Group: Control and Ownership The business group serves as an effective vehicle for centralization of capital precisely because in addition to the control of large quantities of assets not necessarily owned by those who manage it that is afforded by the corporate form itself, the group structure also allows business families to enjoy the benefits of concentrated ownership of the equity of group companies including publicly listed ones. A business group can attain a size far beyond the limits it would be subject to if it were to be primarily dependent on the funds owned directly by its controlling family, limits that family divisions make severer, precisely because of this special combination being its feature. The

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multi-entity structure enables it by allowing business groups to take recourse to the device that in Indian literature has been referred to as inter-corporate investments— units within the group holding the equity of other group companies (Hazari1966; Goyal 1979; Singhania 1980, Rao 1985). In the colonial period, when financial institutions for providing long-term finance were virtually absent and share capital was the principal means of financing industrial investment, companies could be controlled by European and Indian capitalists through managing agency firms.2 After independence, by the time this institution was abolished in 1969, long-term industrial financing of private sector companies was also well on its way to increasingly taking the form of lending by public sector financial institutions. However, Indian business groups by then had also evolved the method of inter-corporate investments to protect themselves from any serious threat to their control. Inter-corporate investments can be said to be a means of creating fictitious share capital—claims on assets that are themselves claims on other assets—that make use of the property-owning rights vested in the units constituting a group. Any funds acquired by any one unit from any source and in any form is potentially usable for the purchase of the equity of another unit rather than any real asset. For instance, a company controlled by a business family could borrow from a bank to finance its acquisition of shares in another company—thus using the borrowed funds to acquire voting rights in the second company that would be controlled by the family but would not ultimately belong to them. Further, the consequent transfer of funds then places the second unit in exactly the same position—in possession of funds that could be used to acquire equity of any other company. Continuous repetition of this process and multiplication of the total share capital of different units can be done without involving any additional funds and indeed the locking up of any funds in this can be eventually eliminated by forming a circular chain of such investments. In the ultimate analysis, all inter-corporate investments within a group would be the liability of some unit (those issuing the shares) as well as the asset of another (those holding the shares). For the group as a whole, these are liabilities that “finance” nothing but their own holding as assets—and consolidation of all the units within the group into a single entity would result in them getting extinguished. It is the creation of fictitious share capital in the form of inter-corporate investments that allows business families to control a much large equity in the group companies than that directly owned by them and through that control also the real and financial assets owned by these companies. It results in a form of separation of capital as property and capital as function that makes that separation appear to be of a lesser order than it actually is—the greater is the proportion of holdings of other corporate bodies in the equity through which group companies are controlled the greater also will tend to be the relative importance of the finance provided by other sources. 2

The managing agency system involved the contractual vesting of the responsibility for managing the affairs of a company to a managing agency, which could be a proprietorship/partnership firm or even a narrowly held joint-stock company. The system was often used to control a single company, but in a managing agency house many companies were managed by a single managing agency firm.

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The use of the device of inter-corporate investments is something possible only if the group includes several different corporate units and this provides one rationale, alongside others, for groups to have a multi-entity structure. Since the mechanism of centralizing control over several corporate units of a business group lies within the structure of the group, it should be also considered as one determinant of that structure. Indeed, this is one possible explanation for the presence of several small private companies within the business group which might otherwise not be performing any function in the organization of its business activities. Again, the pre-1991 history of the Reliance group subsequent to the listing of Reliance Textiles (Industries) can be used to illustrate this. As mentioned earlier, Reliance grew rapidly in the 1980s, for financing which made extensive use of the capital market. For a relatively younger group making its entry into what was still a relatively restricted market, the concentration of production activity and real assets in the one company raising funds was perhaps important because it gave it some scale and size. However, that very success achieved in mobilizing finance and the consequent expansion of the share capital posed the problem of how to maintain and secure the family’s control. As already indicated, and confirmed by Table 5.2, the proportion of the direct holding by the family came down drastically. Reliance solved this problem by recourse to inter-corporate investments but in circumstances when there were no other large companies in the fold to hold a controlling stake in Reliance Industries. How it did so can perhaps explain why there was also the rapid proliferation of companies noted earlier. The evidence (Mazumdar 2006) indicates that several small investment and trading companies created by the group used borrowed funds to repeatedly acquire Reliance shares and that this holding was also periodically transferred from one set of such companies to others. Divestments by some of these companies were accompanied by acquisitions by others through concurrent transactions if not transactions among themselves. Since the acquisitions were also financed by fresh borrowing, this Table 5.2 Distribution of shareholding of Reliance Industries (As on date of annual general meeting of respective years), selected years Year

1977

1982

1987

1988

Total equity shares

5,951,100

16,643,587

51,609,318

152,146,493

Percentage shares held by: Financial institutions

2.94

17.95

12.22

16.68

Bodies corporate

2.94

34.85

36.23

20.47

Directors and relatives

90.29

5.63

2.41

0.81

Other top 50 shareholders

3.83

–

1.65

1.00

Non-resident indians

–

–

–

–

Others

–

41.57

47.50

61.04

Total

100

100

100

100

Source Mazumdar (2006)

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S. Mazumdar

Table 5.3 Structure of ownership of shares of sample of narrowly held Reliance group private companies, 1985 to 1989 Year

1985

1986

1987

1988

1989

Equity shares Number of companies

56

70

81

64

48

Total number of shares

2,149,238

2,743,448

6,830,480

5,587,990

3,751,340

Value of shares (Rs. Lakhs)

220.64

280.25

734.37

563.77

380.10

bodies corporate

33.61

48.20

93.86

91.16

95.96

Individuals

66.39

51.80

6.14

8.84

4.04

Number of companies

24

23

17

16

14

Total number of shares

588,700

581,200

550,100

564,500

551,250

Value of shares (Rs. Lakhs)

60.27

59.52

56.36

57.85

56.52

bodies corporate

82.93

82.79

84.70

81.21

83.17

Individuals

17.07

17.28

15.37

18.86

16.91

Distribution of Ownership (%)

Preference shares

Distribution of Ownership (%)

Source Mazumdar(2006)

was a way of reconciling servicing of debt by individual companies with permanent holding of an expanding number of shares by them as a group—effectively transferring from time to time the group holding of Reliance shares and the debt which financed it from one set of group investment companies to another. As a result, the block holding in Reliance through which it could be controlled shifted away from that held by individuals to that held by investment companies. The debt-equity ratio of the group as a whole was thus considerably greater than that of Reliance Industries because the controlling stake in the latter was basically resulting from routing debt funds through the investment companies. Even the control over these investment companies came to be ultimately based on cross-holding among themselves, so that their principal shareholders were also companies (Table 5.3). The structure of the Reliance group that thus emerged toward the end of the 1980s was one where a complex web of inter-connections through inter-corporate investments and even common directors linked a large number of individually small investment and trading companies, and at any point of time a subs-set among them together held a significant portion of the equity of the publicly listed Reliance Industries which in turn had Reliance Petrochemicals, the only other company that came to be also listed, as one of its three subsidiaries.3 Clearly, the Reliance structure described above was not a product of some spontaneous evolution but a deliberate creation to resolve the problem of control confronting

3

For a visual presentation with names of several companies, see Mazumdar (2017).

5 The Multi-entity Structure and Control in Business Groups

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the group. It was a particular way of using the general form of inter-corporate investments to enable the family to mobilize and control greater capital than it could itself accumulate. With each group adapting that form to its own specific requirements at every point of time, several different kinds of structures are clearly possible. However, none of them can be explained without bringing in the question of how control over capital is organized by business families and the legal and regulatory framework which enables it. Thus, the widespread use of narrowly held investment companies by Indian groups in the pre-liberalization era was known to be a way of circumventing the restrictions on inter-corporate investments that were generally operative at that time. The Reliance case also indicates another important possibility, namely, that apparently stand-alone public companies could very well be part of an inter-connected multi-entity structure forming the basis for control over it. Indeed, there is evidence that, more often than not, this is the case (Mazumdar 2012), which brings into question the validity of classifications into group affiliated and stand-alone companies that form the basis for empirical evaluation of propositions pertaining to business groups and their behavior.

5.4 Liberalization and Control in Business Groups The big fillip to liberal economic reforms after 1991 certainly initiated several important changes in the legal and regulatory framework governing the corporate sector. Curbing the concentration of economic power came to be abandoned even as a formal objective with the abolition of the MRTP Act. The Capital Issues Control Act (CICA), 1947 was also abolished and foreign institutional investors were permitted to invest in the Indian stock market. The Securities and Exchange Board of India was created in 1992 and vested with the responsibility of regulating the market and “protecting the interests of investors in securities” (Government of India 2014, p. 4). The SEBI put in place a takeover code governing acquisitions and changes in control of listed companies. Foreign Direct Investment norms were also liberalized, allowing foreign multinationals to increase equity holdings in their Indian affiliates beyond the limits earlier imposed through the Foreign Exchange Regulation Act (FERA), 1973. Indian companies were also allowed to access international capital markets and then also to invest abroad more freely than earlier. Though the stock market increased in prominence in Indian capitalism as a combined effect of liberalization measures, this development can scarcely be described as one accompanied by a movement in the direction of creating a “market for corporate control” to serve as a mechanism of disciplining corporate managements. Yes, the regulatory environment became more permissive toward acquisitions and opened the possibility of new and powerful raiders from abroad entering the game. However, this only heightened the need for business families to establish more secure control over their group companies, and the regulatory environment also became simultaneously more “liberal” on this count too. Elements in the takeover

120

S. Mazumdar

regulations themselves as well as other regulatory changes provided a more permissive and flexible context for achieving that end of secure control (Varottil 2015). At the same time, foreign firms were also able to exercise greater control over their affiliates. As a result of these, concentration in the ownership of equity of listed companies became even more of a pronounced feature of the Indian corporate sector after liberalization. The takeover regulations introduced in the 1990s gave rise to a new vocabulary, including new meanings to the terms “promoter” and “promoter group” to describe respectively, the controlling authority of a company and the group of individuals and entities who together held the controlling stake. The very idea of a promoter indicated that control over a company was exercised not by the collective of shareholders or even a board of directors or management elected by them. Even the new Companies Act of 2013 acknowledged this in spelling out the meaning of promoter: “69) —Promoter means a person— (a) who has been named as such in a prospectus or is identified by the company in the annual return referred to in sect. 92; or (b) who has control over the affairs of the company, directly or indirectly whether as a shareholder, director or otherwise; or (c) in accordance with whose advice, directions or instructions the Board of Directors of the company is accustomed to act: ” (Government of India 2013, p. 21). Table 5.5 (Appendix) shows the proportion and composition of declared promoter holdings as on 31 March 2018 for the 71 private sector companies (excluding banks and insurance companies) which are part of the top 100 companies in terms of market capitalization in the Bombay Stock Exchange. These 71 companies between them accounted for over 45% of the market capitalization of all companies as on 21 June 2018. A perusal of the last column would show that in general such promoter holdings are quite high relative to the company’s equity base. In the case of 46 companies, its share was more than 50% and in another 20 companies it was greater than 25%. The exceptions where there is no promoter—ITC and Larsen & Toubro—are truly exceptions and even here the former does have a large stake still held by its original parent company. A hostile takeover of the top listed companies is, therefore, clearly an unlikely possibility and as such there is no basis for a stock-market-based disciplining mechanism to work. A look at the composition of promoters’ holdings also makes it clear that the promoter stake is dominated by holdings by other entities (trusts, Indian companies/ LLPs and foreign companies) rather than individuals. Thus, there are barely twelve companies in which the individual holdings of Indians within the promoter group even exceeded 10% of the total share capital. On the other hand, in 58 companies, trusts and Indian and foreign companies within the promoter groups held more than 25% of the share capital.

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The architecture of groups however still varies despite their sharing a common essence. Consider for instance 4 of the largest Indian groups—Tata, Reliance, AV Birla, and Adani. Table 5.4 summarizes the recent position of each group about the number of companies, trusts, or LLPs it has and partial indications of their status. The information used to prepare this table has been taken from the group websites, annual reports of companies where available and the details of promoter shareholding submitted by the listed companies to the Bombay Stock Exchange and available on its website. It is clear from the table that each of the four groups includes within its fold very large number of companies/entities. The declared list of group companies within whom the business activities of the group are distributed is a subset of the total, and their number varies significantly even if we consider only the Indian operations of the groups. From these we get the indication that the main businesses of Reliance continue to be highly concentrated in a few companies while in the Tata group it is the opposite. In each case, the number of companies listed on stock exchanges is even fewer than the number declared as business arms–but even this number has a wide range across the four groups and does not have any obvious relationship with the size of the group or the total number of Indian entities. With regard to the control over companies, each group’s listed companies tend to have several subsidiaries, associate companies, and joint ventures, in which directly or indirectly it is the listed companies that tend to hold a controlling shareholding. While these include other listed companies of the group, unlisted entities are in all cases central to the structure of control over listed companies through their importance in the promoter’s holding in key listed ones. However, here again there are variations. In the case of the Tata companies, the unlisted Tata Sons clearly occupies the position of being an apex holding company of the group. In the Adani group, on Table 5.4 Number and types of companies/entities of four major groups (March 2018) Group

Listed companies

Other companies declared as business arms of the group

Other subsidiaries, JVs or associated companies of listed companies

Other entities in promoter groups of listed companies

Indian

Foreign

Indian

Foreign

Companies/ LLPs

Trusts

Total no. of entities

Adani

4

11

7

116

34

7

3

182 (141)

AV Birla

7

20

26

41

55

19

0

168 (87)

Reliance

2

2

0

119

57

44

3

227 (170)

Tata

22

52

13

119

527

1

4

738 (198)

Source Author’s compilation from information available on the BSE Website, Company websites and Annual Reports

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S. Mazumdar

the other hand, private family trusts have an important role in this (different from the Tata group trusts which are public in nature). A large part of the promoter holding in Reliance Industries is now held by LLPs, but this institutional form doesn’t have a comparable prominence in any of the other three groups. Apart from cross-holding among listed companies, unlisted investment companies appear to be the main ways of building up a controlling promoter’s stake in the AV Birla group. Even when there is no substantive change in control, the entities making up the promoter and the distribution of the holding between them are not necessarily stable over time. The extent of this “mobility” varies across groups and even an individual group can exhibit differences over different time periods. We have seen earlier, how the Reliance controlling shareholding kept changing hands in the 1980s—necessitated by the repeated recourse to capital markets. Such movement in the promoter holding has also happened more recently and independent of any recourse to capital issues. Consider for example the changes in the promoter holding of Reliance Industries that took place between December 2009 and September 2010, in the run up to LLPs becoming major holders of the promoter’s stake.4 Between June 2010 and September 2010, there was no change in the size of the promoter group holding (number of shares held) of Reliance Industries Ltd. Nor was there any change in the composition of the promoter group (the list of individuals/ entities). However, 1,059,170,001 shares changed hands within the promoter group and were transferred from 14 companies to 29 LLPs. This number constituted 72.35% of the total promoter holding and 34.17 of the total share capital of Reliance Industries. Their transfer was declared as inter-se transfers that took place on 11.08.2010, which is perhaps why the open public offer clause of the Takeover Code was not triggered. Since on 11.08.2010, the low and high prices of Reliance shares were Rs. 490 and Rs. 497, respectively, the value of the 1,059,170,001 shares should therefore have been a minimum of Rs. 5189 crores. Of the 1,059,170,001 transferred on 11.08.2010, 987,241,125 shares (or 93% of the total) are also recorded as being sold by 4 companies5 through off-market transactions, and each of them also bought 100 shares on the same day. There was also something, however, that happened before this. These 4 companies did not have these shares to sell in December 2009 as each held only 200 shares at that time and acquired the rest mostly on 31 March 2010 through off-market purchases. On the same day another 5 promoter group companies also sold 780,331,332 through off-market transactions, which could account for 68.71% of the shares bought by the other 4. Thus, even though all the transactions are not being captured in the disclosed information, it is clear that the holdings eventually held by Reliance group LLPs from 4

This discussion is based on the records related to Reliance Industries available on the BSE website (Section on Corporates) – including Disclosures on Shareholding Pattern, Disclosures under SEBI (Prohibition of Insider Trading) Regulations, 1992 (Insider Trading 1992) Disclosures under SEBI (Substantial Acquisition of Shares and Takeovers) Regulations, 2011 (SAST). I am grateful to Mohit Gupta for his inputs and for drawing my attention to this while he was working on his M.Phil dissertation. 5 The four companies, all private limited, were Kshitij Commercials, Kardam Commercials, Nityapriya Commercials and Kankhal Investments and Trading Company.

5 The Multi-entity Structure and Control in Business Groups

123

September 2010 onward had changed hands previously, in the months preceding their acquisition by the LLPs. The 4 companies that accounted for the bulk of this shift to LLPs subsequently ceased to exist, but the available records indicate that these transfers were without any payment being received. This mobility of the controlling stake did not end with the transfer to LLPs. Until a bonus issue in September 2017 doubled it, the size of the promoter holding (number of shares) remained more or less fixed after September 2010 but not necessarily its composition. In fact, another round of significant inter-se transfers happened in March 2017. While all of this can be ascertained from the disclosures mandated by the prevailing regulations, these do not by themselves provide any clue about why the Reliance promoter holding was eventually shifted to LLPs and why did the other moving around of it happen both before and after this change.

5.5 Conclusion The business group structure in India constitutes a particular way of organizing capital that goes beyond the institutional form of the joint-stock company and incorporates within itself the scope for a mechanism through which the “widely held” public company can also be subject to near proprietary control by business families. This structure is always what it is because that is consistent with the objective of ensuring control—a result of the behavior of their controlling business families and not simply its determinant. The business group structure can and does involve the use of companies, firms, and trusts with little public participation. It is a flexible structure characterized by variations as well as a mobility across time. To what extent and in what ways this flexibility and mobility expresses itself is also influenced by the prevailing legal and regulatory framework—the combination of imperatives, constraints, and opportunities it gives rise to—and to the changes this framework experiences from time to time. The period of liberalization has been far from being an exception—indeed, it has afforded more flexibility than was available earlier. The study of business groups—their structures, behavior, and consequences—without reference to this question of control and how it is resolved would therefore be characterized by an important gap. Wider recognition of the existence of this gap is the precondition for the research that would fill it.

Appendix See Table 5.5.

124

S. Mazumdar

Table 5.5 Promoter holdings in major listed non-financial private sector companies (as on March 2018). (Author’s compilation from Shareholding Pattern data of companies available at https:// www.bseindia.com/corporates/Sharehold_Searchnew.aspx) S. No

Company

Promoter holding (Percentage share in total equity) Individuals/ HUF

1

Adani Ports and Special Economic Zone Ltd

2

Aditya Birla Capital Ltd

3

Ambuja Cements Ltd

Foreign individuals

Trusts

42.96

0.06

4

Ashok Leyland Ltd

5

Asian Paints Ltd

6

Aurobindo Pharma 12.32 Ltd

7

Avenue Supermarts 53.56 Ltd

28.64

8

Bajaj Auto Ltd

4.06

0.25

9

Bajaj Finance Limited

0.15

10

Bajaj Finserv Ltd

4.72

11

Bajaj Holdings & Investment Ltd

0.49

12

Bharat Forge Ltd

0.35

13

Bharti Airtel Ltd

14

Bharti Infratel Ltd

15

Biocon Ltd

Indian companies/ LLPs

Foreign companies

Total

6.78

16.52

66.26

71.17

1.53

72.76

63.55

63.55

51.27 10.66

0.03 3.07

52.8

36.48

51.87 82.2

44.98

49.29

54.99

55.14

0.45

53.18

58.35

16.31

27.52

44.32

45.4 50.1

45.75 17.04

67.14

19.77

60.67

53.51 39.77

16

Bosch Ltd

17

Britannia Industries Ltd

18

Cadila Healthcare Ltd

0.01

19

Cipla Ltd

14.08

20

Colgate-Palmolive (INDIA) Ltd

1.13 1.49

53.51 69

70.49

50.7

50.7

74.78 22.37

51.27

42.11

74.79 0.76

37.21 51

51

21

Dabur India Ltd

0.12

67.93

68.07

22

DLF Ltd

2.75

77.83

80.58

23

DR.Reddy’s Laboratories Ltd

2

24.76

26.76

0.02

(continued)

5 The Multi-entity Structure and Control in Business Groups

125

Table 5.5 (continued) S. No

Company

Promoter holding (Percentage share in total equity) Individuals/ HUF

Foreign individuals

Trusts

Indian companies/ LLPs

Foreign companies

Total

24

Eicher Motors Ltd

2.28

2.24

45.92

0.06

50.5

25

Godrej Consumer Products Ltd

2.64

0.28

0.47

59.86

63.25

26

Grasim Industries Ltd

0.13

27

Havells India Ltd

15.2

28

HCL Technologies Ltd

29

Hero Motocorp Ltd.*

14.19

20.44

30

Hindalco Industries Ltd

0.11

33.92

31

Hindustan Unilever Ltd

36.31 3.02

3.65

41.36 43.38

40.09 59.58

16.8

60.18 34.63

0.65

34.68

67.19

67.19

32

Hindustan Zinc Ltd

64.92

64.92

33

Indiabulls Housing 0.11 Finance Ltd

22.68

22.79

37.9

74.93

34

Infosys Ltd

12.9

35

InterGlobe Aviation Ltd

0.35

12.9 23.08

13.6

36

ITC Ltd.**

37

JSW Steel Ltd.

38

L&T Finance Holdings Ltd.

64.01

64.01

39

Larsen & Toubro Infotech Ltd.

82.96

82.96

40

Larsen & Toubro Ltd

0 0.6

38.7

2.07

41.37

0

41

Lupin Ltd.

42

Mahindra & Mahindra Financial Services Ltd.

43

Mahindra & Mahindra Ltd.

0.63

0.09

8.85

44

Marico Ltd.

12.15

0.14

46

45

Maruti Suzuki India Ltd.

1.25

45.48

0.28

47.01

51.19

51.19

12.15

21.72

1.42

59.71 56.21

56.21 (continued)

126

S. Mazumdar

Table 5.5 (continued) S. No

Company

Promoter holding (Percentage share in total equity) Individuals/ HUF

46

Foreign individuals

Motherson Sumi Systems Ltd.

0.53

2.32

11.46

0.62

Trusts

1.25

Indian companies/ LLPs

Foreign companies

Total

33.43

4.97

41.25

47

MRF Ltd.

48

Nestle India Ltd.

14.21 62.76

62.76

27.54

49

Oracle Financial Services Software Ltd.

73.82

73.82

50

Page Industries Ltd.

51

Pidilite Industries Ltd.

50.42

2.18

17.17

69.77

52

Piramal Enterprises Ltd.

0.38

45.99

5.01

51.38

53

Procter & Gamble Hygiene & Health Care Ltd.

54

Reliance Industries 0.69 Ltd.

55

Shree Cement Ltd.

56

Shriram Transport Finance Co.Ltd.

57

Siemens Ltd.

58

Sun Pharmaceutical Industries Ltd.

12.22

59

Sun Tv Network Ltd

75

60

TATA Consultancy Services Ltd.

49.01

49.01

1.91

3.91

3.08

68.73

42.85

47.45

61.7

64.78

26.08

26.08 75

0.05

70.64

42.11

75 54.38

75 71.92

71.92

61

TATA Motors Ltd.

36.37

36.37

62

TATA Steel Ltd.

0.07

33.14

33.21

63

Tech Mahindra Ltd.

9.8

26.17

64

Titan Company Limited

65

Ultratech Cement Ltd.

0.03

0.02

35.99

52.91

52.91

60.95

60.98 (continued)

5 The Multi-entity Structure and Control in Business Groups

127

Table 5.5 (continued) S. No

Company

Promoter holding (Percentage share in total equity) Individuals/ HUF

66

United Breweries Ltd.-$

67

United Spirits Ltd.

0.01

UPL Limited

0.57

69

Vedanta Limited WIPRO Ltd.***

71

ZEE Entertainment Enterprises Ltd.

Trusts

8.08

68 70

Foreign individuals

1.95

Indian companies/ LLPs

Foreign companies

Total

21.39

43.88

73.35

3.69

54.78

25.2 50.13

4.22

13.67

56.43 25.21

58.48 27.72 50.13 74.32

16.41

41.62

*Individual holdings are mainly through partnership firm **BAT Group holds 29.71 percent of the total equity ***Indian company holdings are mainly by proprietorship/partnership firms

References Amsden AH, Hikino T (1994) Project execution capability, organizational know-how and conglomerate corporate growth in late industrialization. Ind Corp Chang 3:111–147 Basu SK (1958) The managing agency system. In: Prospect and retrospect. The World Press Pvt. Ltd., Calcutta Ghemawat P, Khanna T (1998) The nature of diversified business groups: a research design and two case studies. J Indus Econ 46(1):35–61 Government of India (1964) Committee on distribution of income and levels of living (Mahalanobis Committee) report. Planning Commission, Government of India, New Delhi Government of India (1965) Monopolies inquiry commission (MIC) report. Government of India, New Delhi Government of India (1969) Industrial licensing policy inquiry committee (ILPIC) report. Department of Industrial Development, Ministry of Industrial Development, Trade and Company Affairs, Government of India, New Delhi Government of India (2013) The companies act, 2013. http://www.mca.gov.in/Ministry/pdf/Com paniesAct2013.pdf. Accessed 23 January 2019 Government of India (2014) Securities and exchange board of India Act, 1992 [As amended by the Securities Laws (Amendment) Act, 2014]. https://www.sebi.gov.in/sebi_data/attachdocs/ 1456380272563.pdf. Accessed 23 January 2019. Goyal SK (1979) Monopoly capital and public policy. Allied Publishers Private Limited, New Delhi, Bombay, Calcutta, Madras, Bangalore, Hyderabad Granovetter M (1995) Coase revisited: business groups in the modern economy. Ind Corp Chang 4(1):93–129 Guillén MF (2000) Business groups in emerging economies: a resource-based view. Acad Manag J 43(3):362–380 Hazari RK (1966) The structure of the private corporate sector: a study of concentration. Asia Publishing House, Bombay, Ownership and Control Joshi LA (1965) The control of industry in india: a study in aspects of combination and concentration. Vora and Co. Publishers Pvt. Ltd, Bombay

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Khanna and Yafeh, 2007 Khanna T, Yafeh Y (2007) Business groups in emerging markets: paragons or parasites. J Econ Literat 45(2):331–372 Khanna T, Palepu K (2007) The evolution of concentrated ownership in India: broad patterns and a history of the Indian software industry. In: Morck RK (ed) A history of corporate governance around the world: family business groups to professional managers, Paperback. University of Chicago Press, Chicago, pp 283–320 Kothari ML (1967) Industrial combinations: a study of managerial integration in Indian industries. Chaitanya Publishing House, Allahabad Leff NH (1978) Industrial organization and entrepreneurship in the developing countries: the economic groups. Econ Dev Cult Change 26(4):661–675 Mazumdar S (2006) Business groups and concentration in the private corporate sector in India (unpublished thesis). Jawaharlal Nehru University, New Delhi Mazumdar S (2012) The Indian corporate structure and the ‘theory’ of emerging market business groups. Hist Sociol South Asia 6(2):87–109 Mazumdar S (2017) From ‘outsider’ to insider: the case of reliance. South Asia Multi-Discipl Acad J http://journals.openedition.org/samaj/4278. https://doi.org/10.4000/samaj.4278. Mehta MM (1952) Combination movement in Indian industry (A study of concentration of ownership, control and management in Indian industries). Friends’ Book Depot, Allahabad. Mohnot SR (1962) Concentration of economic power in India: a statistical study of concentration and diffusion of economic power in India. Chaitanya Publishing House, Allahabad Namjoshi MA (1966) Monopolies in India: policy proposals for a mixed economy. Lalvani Publishing House, Bombay-Calcutta-Madras-New Delhi Nigam RK, Chaudhuri NC (1960) The corporate sector in India, a factual presentation of long and short-term trends. Research and Statistics Division, Department of Company Law Administration, Ministry of Commerce and Industry, Government of India, New Delhi Nigam RK, Joshi ND (1963) The pattern of company directorships in India, 2nd Edn. Research and Statistics Division, Department of Company Law Administration, Ministry of Commerce and Industry, Government of India, New Delhi Nigam RK (1959) Managing agencies in India (First round: basic facts). Department of Company Law Administration, Ministry of Commerce and Industry, Government of India, New Delhi Rao KSC (1985) Inter-connections under the MRTP act in the context of asset limit hike. Econ Pol Wkly 20(27):1132–1146 Singhania VK (1980) Economic concentration through inter-corporate investments. Himalaya Publishing House, Bombay Varottil U (2015) The nature of the market for corporate control in India. In: NUS Law Working Paper 2015/011, December 2015. www.law.nus.edu.sg/wps/. Accessed 22 June 2018

Chapter 6

Business Group Affiliation, Financial Distress and Corporate Investment-Cash Flow Sensitivity: Evidence from India Jitendra Mahakud and Gaurav Gupta

Abstract This study explores the role of business group affiliation and financial distress on determination of corporate investment policy of the manufacturing companies in India. We find that the firm specific variables like cash flow, Tobin’s Q ratio, sales income, age of the company, financial leverage are the major determinants of corporate fixed investments. Companies affiliated to a business group invest more in the fixed assets than the standalone companies. Group affiliation reduces the impact of cash flow in determining corporate fixed investment. The results indicate that financial distress plays a negative role in the determination of corporate investment. We also find that financial distress does not affect the investment-cash flow sensitivity of the affiliated firms in India. The results are robust across the periods and different types of companies.

6.1 Introduction Several empirical studies on investment-cash flow sensitivity show their strong support to the fact that the internal cash flow has a positive impact on investments undertaken by the firm, and the impact is more for the more financially constrained firms than the less financially constrained firms (Hoshi et al. 1991; Calomiris et al. 1994; Gilchrist and Himmelberg 1995; Kadapakkam et al. 1998; Aivazian et al. 2005; Ahn et al. 2006; Ascioglu et al. 2008; Attig et al. 2012). The impact of group affiliation on investment-cash flow sensitivity has gained attention in the recent years as the financing behavior of affiliated firms is different from the stand alone firms. A business group can be regarded as an association of legally independent firms (Leff 1978) and also be defined as a set of firms bound by strategic alliances. The group J. Mahakud (B) Department of Humanities and Social Sciences, Indian Institute of Technology, Kharagpur, India e-mail: [email protected] G. Gupta FORE School of Management, New Delhi, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_6

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affiliated firms are linked through family ownerships and financial inter-linkages. Several explanations have been proposed to understand the significance of business group affiliations in the corporate finance literature (Ghemawat and Khanna 1998; Khanna and Palepu 1999a, b, 2000a, b; Chang and Hong 2000; Khanna and Rivkin 2001). Business group affiliations may reduce information asymmetry in the member firms (Dewenter and Warther 1998). The inter-linkage between business group affiliation and corporate investments is derived from the argument that in an inefficient capital market, when it is difficult and costlier for the firms to raise external capital, business groups may play a major role in generating and allocating funds to investment projects through internal capital market, and, it is also less costly for the group affiliated firms to raise financial capital from the market due to their reputation and better access (Lensink et al. 2003). Prior empirical studies have mostly analyzed the role of financial constraints on corporate investment decisions (Kaplan and Zingales 1997; Fazzari et al. 1988; Cleary 1999). A recent study by Bhagat et al. (2005) documents that “financially distressed firms behave differently than financially constrained firms” which depicts that the condition of financial constraints is not directly imposed on the financially distressed firms while firms in financial distress may come under the financial constraints due to the external financing problems. A firm becomes financially distressed when it faces difficulties to meet the principal and interest obligations or the extreme case being bankrupt (Fazzari et al. 1988). Further, financially distressed firms face difficulties in borrowing capital from the external market due to the attitude of lending agencies, banks and financial institutions. This could be due to that market lending agencies do not trust the financially distressed firms as these firms are already struggling to pay their previous loans. Additionally, Lindner and Jung (2014) also document that lenders may choose not to roll over debt, or not to provide new credit to the companies that may become distressed. As a result, distress firms start selling their assets to meet their debt obligations which in turn affect the profitability, availability of internal funds and assets. Firms also start facing external borrowing constraints and finally, their investment policy gets affected. Therefore, a negative association can be expected between investment undertaken by the firm and financial distress condition. Further, we hypothesize that the effect of financial distress may have less effect on investment-cash flow sensitivity of business group affiliated firms than the standalone firms. Khanna and Danielle (1997) find that, in India, business groups form an important part of the private sector and group affiliated firms are associated with more than 80 percent of the private sectors’ assets, profit and sales in the year 1993. Indian business groups are largely diversified and usually have a large proportion of family ownerships. The Indian companies affiliated to a business groupmostly linked through cross-holdings of equity and mutual board representations. There are more than 400 business groups existing in India and group affiliation has the implications for various corporate finance decisions. In this regard, the companies operating in India have been considered as the ideal sample for providing an out of sample evidence on this issue.

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The rest of the chapter is organized as follows: Sect. 6.2 discusses literature review. Section 6.3 presents variables and data. Section 6.4 specifies the models and econometric method. Section 6.5 presents the results and Sect. 6.6 provides the summary and conclusions.

6.2 Literature Review The literature review deals with the various theories and empirical evidences on determinants of corporate investments. This section is divided into two broad sub sections. The first sub-section briefly discusses the various theories of corporate investments. The second sub-section reviews the empirical literature on the determinants of corporate investments, and the impact of financial distress and business group affiliation on corporate investments.

6.2.1 Theories of Corporate Investment According to Keynes (1936) and Fisher (1930) as long as the expected return on investment is above the opportunity cost of capital, investment will be worthwhile. Return on investment is equivalent to Keynesian concept of marginal efficiency of the capital and the concept of internal rate of return is given by Fisher. According to Keynes (1936) investments are made until “there is no longer any class of assets of which the marginal efficiency exceeds the current rate of interest”. The Keynesian theory argues that investments are not determined by the underlying capital stock due to the uncertainty irrational and volatile expectations of the market participants. On the other hand, Fisher (1930) and Hayek (1941) regarded investment as an optimal adjustment path towards an optimal stock. All other theories of investment are derived from the principle of either Keynes or Fisher. There are basically three major theories of corporate investment such as neoclassical theory, accelerator theory and Tobin’s Q theory.

6.2.2 Neoclassical Theory of Investment Neoclassical theory of investment proposed by Jorgenson’s (1963) which basically formalizes the arguments and ideas put forward by Fisher (1930). According to this investment theory, maximizing profit in each period always yields an optimal capital stock and the capital adjusts immediately and completely to the desired capital stock. The investment becomes the change in capital between the two periods. This theory basically argues that the desired capital stock is determined by output, price of output and user cost of the capital and therefore, it considers that these variables

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or factors are the major determinants of corporate investment. Further, this theory is divided into two models. The first model is based on the concept of the user cost of the capital which states that firms’ user cost of capital and level of output are major determinants of a corporate investment. The second model is linked with the theory of profit maximizing firm and firm’s production function, which create a technical relationship between the inputs and outputs. The model undertakes flexible accelerator prices and capital markets.

6.2.3 Accelerator Theory of Investment The idea of the accelerator theory or principle came from Clark (1917). It is assumed that accelerator theory of investment theory is a special case of the neo-classical theory of investments where the price variable has been reduced to a constant. Therefore, the desired capital stock is assumed to be proportional to output. Investment in any period will therefore depend on the growth of the output. In other words, this theory upholds that companies adjust their stock of capital in response to demand from which it can be inferred that the investment of companies has a direct relationship with the output. In this context, firms’ investments are proportional to sales or output that confirms that the sales or the output are the major determinants of corporate investment.

6.2.4 Tobin’s Q Theory of Investment Neoclassical theory and accelerator theory of investment have certain fundamental problems such as (i) the adjustment of capital stock is to the desired level is instantaneous and complete in each period which is not basically the possibility, and (ii) existence of expectations may have no role in neoclassical theory and accelerator theory. Brainard and Tobin (1968) and Tobin (1969) proposed a solution which explains that the investment should be made until the value of market value of assets is equal to the replacement cost of assets. According to this theory, investment opportunities are measured by the market value of capital stock. In sum, firms’ investment spending has a positive relationship with Tobin’s Q. The basic idea behind this theory is that the equity market can capture the investment opportunities of the firms. Further, it states that firm’s investment is dependent on the relationship between the value of the firm and the cost of new or replacement capital where the replacement cost is defined as the price that a firm would pay to replace a present asset at the current market price with the same type of assets. This theory emphasizes that the stock market plays a major role in determination of corporate investment.

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6.2.5 Empirical Evidence This sub-section presents a review of empirical studies on the issues like role of cash flow on corporate investments, identification of other firm specific factors which determine the corporate investments, impact of financial distress on corporate investments and effect of group affiliation on investment-cash flow sensitivity.

6.2.6 Cash Flow and Corporate Investments The Q-model of investment assumes that in the perfect capital market the internal and external funds are perfect substitutes and therefore, the investment decision of a firm solely a function of investment opportunities and invariant to the firms’ cash flow. In the imperfect market condition external funding is costlier than internal financing because of frictions arising from asymmetric information, agency problem and transaction costs. Under such conditions, firms’ investments are mostly affected by the availability of internal funds. Among the early empirical studies Fazzari et al. (1988) have shown that financial constraints have been the major factor which affects the corporate investment in the US market. Since the seminal work of Fazzari et al. (1988), numerous studies have assumed that the existence of financial constraints can be deduced from a positive relationship between the availability of internal cash flow and investment (e.g. Hoshi et al. 1991; Caggese 2007). Basically, the importance of cash flow has been presented in the financing hierarchy hypothesis, i.e. “pecking order” theory of financing proposed by Myers (1984). The pecking order theory explains that the firm’s capital structure will be pushed by the desire to finance new investments, first internally, then with low-risk debt, and finally with equity only as a final recourse. In this context, information asymmetries or transaction costs induce a cost premium that makes external finance an imperfect substitute for internal finance. In a specific manner, the corporate fixed investment may depend on the financial factors, such as the availability of internal finance, access to new debt or equity finance, or the functioning of particular credit markets. Therefore, availability of internal fund is one of the major determinants of corporate investments. Most of the studies find evidence for developed as well as emerging economies that the investment-cash flow sensitivity has been more for the financially constrained firms1 than for the unconstrained firms (see for example, Kadapakkam et al. 1998; 1

Fazzari et al. (1988) have classified firms to whether they were likely to be financially constrained on the basis of dividend payout ratio. High dividend payout ratio firm’s check can effortlessly get financial capitals from the market, if required. Therefore, paying dividends is likely to be a major indicator of a firm’s ‘good health’, signalling long-term growth prospects. Fazzari et al. (1988) have also argued that firms use available internal funds to distribute dividends, which demonstrate that these firms face no or fewer costs related to imperfections on the capital markets and treated as least financially constraints firms than that of firms that uses their lower cost of internal fund to finance their investment or have lower dividend payout ratio. The highest sensitivities to cash flow are found for firms categorized as financially constrained, and this is taken to indicate that financial

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Goergen and Renneboog 2001; Laeven 2003; Bhaduri 2005; Shen and Wang 2005; Ghosh and Ghosh 2006; Degryse and De Jong 2006; Aggarwal and Zong 2006; Cleary et al. 2007). Devereux and Schiantarelli (1990) and Schaller (1993) find that cash flow effects are important for smaller and young firms. Whited (1992) finds that investment is more sensitive to cash flow in firms with high financial leverage than the firms having low financial leverage. Houston and James (1996) find that investment-cash flow sensitivity is higher for firms that are closely tied to a single bank than the firms that have relationship with several banks. On the other hand, using Tobin’s Q model, Kaplan and Zingales (1997, 2000) show that firms that appear less financially constrained exhibit significantly greater sensitivities towards the fixed investments than the firms that appear more financially constrained. Cleary (1999) also used large data set and showed that the highly constrained firms have the lowest investment-cash flow sensitivity. Using a panel of 24,184 the UK firm over the period 1993–2003, Guariglia (2008) has found that the sensitivity of investment to cash flow tends to increase monotonically with the degree of external financial constraints faced by firms. Hobdari et al. (2009) examine the determinants of investment of manufacturing firms in Estonia with the annual firm level observation of the data set consisting of 4218 observations over the period 1993–2002. This study revealed that financially constrained firms are more sensitive to the availability of internal finance, while financially nonconstrained firms are more responsive to future growth opportunities. Hovakimian (2011) and Ben Mohamed et al. (2014) support the fact that cash flow has a positive relationship with investment and the financing constraints affect the investment. La Rocca et al. (2015) used a cluster analysis and find investment to be highly sensitive to cash flow for financial constraint firms. Riaz et al. (2016) report that investment-cash flow sensitivity has increased monotonically with the level of financial constraints and also, investment-cash flow sensitivity for the constrained group is much higher as compared to the unconstrained group. Mulier et al. (2016) report that constrained firms display the highest investment-cash flow sensitivities. The study of Li et al. (2017) depicts that larger and more mature firms are less financially constrained but have higher investment-cash-flow sensitivity. Gupta and Mahakud (2019, 2020) and Gupta et al. (2021, 2022) documented that cash flow plays a significant role in corporate investment decisions and the role of cash flow for corporate investment is also affected by financial development, macroeconomic condition, economic policy uncertainty and the CEO’s education.

constraints are binding in this case. Many further studies have followed the same methodology including Chirinko and Schaller (1995), Hubbard et al. (1995) as summarized by Hubbard (1998). Apart from this, several criteria have been used to classify firms as financially constrained, such as debt (Kaplan and Zingales 1997; Cleary 1999), cash stock (Kaplan and Zingales 1997; Povel and Raith 2001), cash flow volatility (Cleary 2006) and age (Devereux and Schiantarelli 1990; Oliner and Rudebusch 1992).

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6.2.7 Other Firm Specific Factors and Corporate Investments Sharpe (1994), Aivazian et al. (2005), Ahn et al. (2006), have shown the importance of leverage on the determination of corporate fixed investments and this study finds a negative relationship between leverage and corporate investment. Hubbard (1998), Chava and Roberts (2008) highlight the significance of debt covenants on corporate investment. Carpenter and Guariglia (2008) find that corporate investment decisions are largely influenced by companies’ growth opportunities and financing capacity. Using the data for Australian Companies, La Cava et al. (2005) find that real sales, the user cost of capital, cash flow and availability of internal funds have been the major determinants of corporate investments during the period 1990 to 2004. This finding was also supported by Bond and Meghir (1994). Rajakumar (2005) finds that the financial (economic) sector reform cost, liquidity, leverage, availability, and allocation of fund affect the corporate investment of the Indian firms during the period 1988–89 to 1998–99 and the findings are consistent with the accelerator theory, Tobin’s q theory and liquidity theory of investment. Bhaduri (2005) investigated the impact of financial liberalization on the investment patterns of Indian companies during the period 1989–1990 to 1994–1995 and concluded that the small and young firms experienced a significant increase in financial constraints in the post liberalization period, which in turn reduced their investments. Das and Senapati (2007) have found that the companies’ profit and input prices significantly affect the corporate fixed investment in India. Bhattacharyya (2008) also examines the determinants of corporate investment after the post liberalization period and finds that internal liquidity, profitability, and firms’ financial strength are the major determinants of corporate investment. The findings are consistent with neoclassical theory of investment. Vijayakumar (2009) has concluded that industry class, size, and profitability are the most significant factors affecting corporate investment. Following the accelerator, neoclassical, Tobin’s Q and liquidity theories of investment and considering a data set for 897 firms during the period 2000–01 to 2008–09 Jangili and Kumar (2010) have found that firms’ size, cash flow, growth in value of production and capital market development have positive relation with investment and cost of borrowing (lending rates of banks), and real effective exchange rate at the macro level is negatively related to corporate investment of Indian companies. As information asymmetric problem and financing constraints vary across the age of the firm it also affects corporate investment decision (Devereux and Schiantarelli 1990; Oliner and Rudebusch 1992; La Rocca et al. 2015). As young firms are more financially constraint, corporate investment has an inverse relationship with the investment behavior. Tokuoka (2012) has shown that company specific variables like profitability, liquidity and leverage have been the major determinants of corporate investments in India. Flor and Hirth (2013) document that asset liquidity plays a major role in the determination of corporate fixed investment. Chen et al. (2013) examine bank debt-investment behavior of Chinese manufacturing firms during the period 2008–2010 and conclude that debt-investment relationship is significantly negative for high-growth firms, but not significant for low growth firms.

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Datta and Agarwal (2014) have studied the corporate investment behavior during bull, bear and different liquidity phases for the period 1998–2012 and found that firm specific factors like profitability, firm size, growth opportunity, tax, non-debt tax shield, tangibility and cash and bank borrowings and macroeconomic factors like interest rate, gross fiscal deficit and economic growth measured by change in per capita income have been affecting the corporate fixed investments in India. A recent study by Ajide (2017) examines the effect of institutional and firm-specific factors on corporate investment in Nigeria using quoted non-financial firm within the period of 2002–2012. This study reveals that institutional quality does not affect investment but firm specific factors do. Their study postulates that cash flow and leverage have positive and negative relationship with corporate investment.

6.2.8 Business Group Affiliation and Corporate Investments Earlier studies have shown that business groups support the companies to raise external capital when the capital markets are imperfect or in the presence of external market failure (Leff 1976, 1979; Aoki 1990; Bergolf and Perotti 1994; Weinstein and Yefeh 1998). Specifically, business groups play an intermediate role in the inefficient capital market (Lomnitz and Parez-Lizaur, 1987; Pan, 1991). Ghemawat and Khanna (1998) state that business group affiliation increases the capacity of the firms to access policy makers which help them to access the external capital easily. In this context, Fisman and Khanna (2004) and Khanna and Palepu (1999a, b, 2000a, b) document that business groups in India and Chile have enhanced the value of the company through labor, product, and capital market intermediation. Khanna and Palepu (2000a) have shown that the greater access to foreign technology and foreign capital by the business group firms also aid to increase the access to the external capital. Similarly, Chang and Hong (2000) document that business group firms can share group wide reputation and thus increase their access to the external market. Gopalan et al. (2007) have investigated the internal capital market of Indian businesses and they reveal that group loans are largely used to help the members in situations of financial distress. Gopalan et al. (2014) have also argued that business groups created a virtual or internal capital market that reduces the firms’ dependence on external capital. Gupta and Mahakud (2018) find that business group affiliation affects investment-cash flow sensitivity.

6.2.9 Financial Distress and Corporate Investment Although there are many proxies used to measure financial distress, three of them have been used extensively by earlier literature, which are Altman’s Z-score (Nash et al. 2003; Denis and Mihov 2003; Zulkarnain et al. 2001; Khaliq 2014; LopezGutierrez et al. 2015; Vosoughia et al. 2016), financial distress ratio (Bhagat et al.

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2005; Wruck 1990; Asquith et al. 1994; Andrade and Kaplan 1998; Pindado et al. 2008; Whitaker 1999 Lopez-Gutierrez et al. 2015) and Ohlson’s O Score model (Bhagat et al. 2005; Lopez-Gutierrez et al. 2015). Prior research has investigated the relationship between financial distress and firm performance. The study of Opler and Titman (1994) reveals that increase in financial distress condition reduces the firm performance. Using the data of Swedish firms Asgharian (2003) finds that under distressed condition highly leveraged firms face relatively lower stock returns. Tan (2012) also investigates the impact of financial distress on the performance of Asian economies and finds that firms with low financial leverage tend to perform better than firms with high financial leverage. Additionally, the financial crisis magnifies the adverse impact of financial distress on firm performance. John (1993) find that firms, which have survived from financial distress, increase their investments. Andrade and Kaplan (1998) explore that financially distressed firms with positive operating income have reduced their capital expenditures and sold their assets at low prices, but these firms do not agree to accept any riskier investment projects. Ogawa (2003) examines the behavior of firms’ investment in Japan and finds that financial distress seriously affects firms’ investment in 90 s where the firms’ leverage had negative and significant relationship with investment for small firms. Bhagat et al. (2005) examine the investment-cash flow sensitivity of financially distressed firms and find that the relationship between investment and internal fund is controlled by operating profits. This study finds that distressed firms invest less, have lower cash flow, high leverage and grow less than non-distressed or healthy firms. This study also argues that financially distressed firms behave differently from financially constrained firms where financially constrained firms invest more, hold larger cash flows, a larger operating income and lower leverage, and high sales growth than lesser constrained firms, but financially distressed firms invest less, have smaller cash flows, lower operating income, high leverage, and a lower sales growth than more constrained firms. Bassetto and Kalatzis (2011) find that financially distressed firms showed higher investment-cash flow sensitivity. This study also finds that as the firms become more financially distressed they keep more cash holding, probably to avoid losses of future investment opportunities. The more-capital-intensive firms with higher cash holding and lower profitability suggest that these firms are exposed to severe agency conflicts, showing higher volatility to external financing costs and are more financially constrained. Maripuu and Mannasoo (2014) have found that firm specific factors like liquidity, leverage and profitability play the significant role for the determination of corporate investments for the financially distressed firms. Considering the 4029 non-financial firms of different countries like Germany, Canada, Spain, France, Italy, UK and US for the period of 1996–2006, LopezGutierrez et al. (2015) find that financially distressed firms invest less than the healthy firms and investment behavior is not uniform for all the financially distressed firms and propensity to underinvestment depends on the investment opportunities available to the companies. This study concludes that firms with greater opportunities have additional investments that can help them to overcome their difficulties. Gupta and

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Mahakud (2022) find that financial distress increases investment-cash flow sensitivity and negatively affects corporate investment.

6.3 Variables, Data and Preliminary Evidence 6.3.1 Variables Following the literature review, we use corporate fixed investments as the dependent variable and identify various factors, which may affect this corporate fixed investment in India in this section. Corporate Investment (I /K ): Following Fazzari et al. (1988), Whited (1992), Gupta et al. (2018) and Gupta and Mahakud (2019, 2022) corporate fixed investment has been measured as the change in fixed assets (current year fixed assets—previous year fixed assets) divided by previous year fixed assets. The following notations are used to explain this variable, which is used as the dependent variable in this study. (/ ) K t − K t−1 It I = K it = K K t−1 t−1 Here, I = net investments, K = current year fixed assets which include plants, property and equipment, K t−1 = previous year fixed assets. The subscripts i, and t, represent the firm and time respectively. The a priori determinants of corporate investments and their expected relationship with corporate investment are explained as follows: Lagged Investment (I /K it−1 ): It is explored that there is a persistent effect of previous year investment on the current year investment (Laeven 2003; Love 2003; Ratti et al. 2008; Gupta et al. 2018; Gupta and Mahakud 2019, 2022). These studies have argued that the company’s current year investment behavior is highly influenced by the previous year investment. We expect a direct relationship between lagged investment ratio and current investment ratio. Tobin’s Q Ratio ( Q): Tobin’s Q ratio shows the availability of growth opportunities in the market. This variable explains that if Q ratio is greater than one, companies can make additional investment in different projects because the earnings made would exceed the cost of firm’s assets. If Q is less than one, the companies would be better off to sell their assets rather than trying to put them to use. Firms with high growth opportunities always invest more than the firms with low growth opportunities (Fazzari et al. 1988; Hiller et al. 2010; Gupta and Mahakud 2019, 2022). It is measured as the market value of assets to the book value of existing assets. We expect a positive association between Q and investment.

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Sales (S/K ): Sales can be considered as the indicator of firm growth and strength of firms to remain in the market. Sales also can be used a proxy for continuation of firm production and operation. It is also assumed that there is a positive association between sales and profitability. We hypothesize that sales has the positive impact in investment decisions. In this study we use the net sales and scaled it by the beginning year capital. Cash Flow (C F/K ): Cash flow is the amount of money in excess of that needed to finance all positive net present value projects. The purpose of allocating money to projects is to generate a cash flow in the future, which should be significantly greater than the amount invested. Therefore, we expect a positive relationship between cash flow and investment. Following Fazzari et al. (1988), Guariglia (2008), Jangili and Kumar (2010), Gupta et al. (2018), Gupta and Mahakud 2019, 2022), we measure cash flow as the summation of profit after tax and depreciation and scaled by beginning year capital. Interest Expenses (T I E/T B): The investments can be funded through either equity or debt. Firms may undertake new investments when the interest rates are low. On the other hand, firms may defer their investment proposals when the interest rates are high. Also, it is assumed that cost of borrowings or the user cost of capital should be less than the rate of return on the investment. Therefore, we assume that interest expenses or cost of borrowings should be negatively associated with investment. Following Rajakumar (2005), Jangili and Kumar (2010), La Cava et al. (2005), Gupta et al. (2018) and Gupta and Mahakud 2022), we measure cost of borrowings as the ratio of the total interest payments to total borrowings. Liquidity (L I Q): The liquidity position of a firm is directly associated with investment decisions. It shows that if a firm has more liquid assets then it will make easy for the firms to finance their current investment. The current ratio is used to measure the liquidity position of a company, and it is defined as the ratio of current assets to current liabilities and we expect a positive relation between liquidity and investment decisions. Leverage (L EV ): Debt financing of the firm has certain fixed obligations such as the payment of fixed interest and principal. The failure of these payments increases the bankruptcy and liquidation cost. Higher levels of debt result in an increased probability of financial distress and the demand for higher returns by potential suppliers of funds. Highly levered firms are less likely to exploit valuable growth opportunities as compared to firms with low levels of leverage (Myers 1977). Therefore, we expect that leverage should be negatively associated with corporate investment. Following Lang et al. (1996), Aivazian et al. (2005), Hiller et al. (2010) Gupta et al. (2018), Gupta and Mahakud (2022), we use debt to total assets ratio as the proxy for leverage ratio. Firm Size (SZ): Larger firms have relatively better access to capital market and find it easier to raise external funds from capital markets with lower cost and fewer constraints as compared to small firms, which increases the probability of more

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investment for large size firms (Higgins 1972). Therefore, a direct relationship is expected between the firm’s size and the corporate investment decision. Following Fazzari et al. (1988), Jangili and Kumar (2010), Gupta et al. (2018), Gupta and Mahakud (2022), we use the natural logarithm of total assets as a proxy to measure firm size. Tangibility (T AN): The high proportion of tangible assets assures greater degree of protection to the bondholders, which in turn helps to reduce the conflict between the shareholders and bondholders and also to reduce the agency cost (Titman and Wessels 1988). Assets that are more tangible sustain more external financing, which increases the firm’s ability to investment more when investment demand is constrained by capital market imperfections (Almeida and Campello 2007). Following Alli et al. (1993), Almeida and Campello (2007), Mollah (2011), we have measured tangibility of assets as the net fixed assets scaling total assets and expect a positive relationship between tangibility and corporate investment decisions. Firm Age ( AG E): Young firms are relatively new in the market than the matured firms and also matured firms have more reputation and strong connection with their lending agencieswhich help them avail external financing (La Rocca et al. 2015). Easy availability of external financing increases the probability of investment spending. Therefore, we expect that firm age is positively related with corporate investment. We use the natural logarithm of firm age where the age has been measured as the current year minus the incorporation year of the firm. Business Group Affiliation (BG A): Business group firms are different than the standalone firms because group firms share internal capital market, technology, and risk (Khanna and Palepu 1999a, b; Khanna and Palepu 2000b; Khanna and Yafeh 2005). Also, Group affiliated firms are generally not financially constrained due to the existence of internal capital market and it is easier for the affiliated firms to borrow from the external capital market because of their reputation and political connection (Lensink et al. 2003). These special characteristics of business group help affiliated firms to invest in the profitable projects even if firms are suffering from lack of internal fund. We expect a positive relationship between business group affiliation and corporate investment. Following Gupta and Mahakud (2018, 2022) the firm, which belongs to the business group is considered as a group affiliated company and is represented by dummy variables (1) and the firm not belonging to any business group is considered as the standalone firm represented by the dummy (0). Following Bhagat et al. (2005), Lopez-Gutierrez et al. (2015) we use three proxies (1) Altman’s Z-Score model (FDA), (2) Financial distress ratio (FDB)and (3) Ohlson’s bankruptcy probability model(FDC) as the measures of financial distress. Altman’s Z-Score model (FDA): Altman (1968) developed a model known as Z Scoremodel considered as the most effective method of measuring the financial distress to access the financial health of non-U.S. companies. Altman (2002) describes the value of Z’ Score has the following intervals. A value higher than 2.6is considered the “safe zone”, and implies the possibility of bankruptcy. Values between 1.1 and 2.6 are considered the “gray zone” or “zone of ignorance”, because

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of the susceptibility to error classification. Values under 1.10 are considered “distress zone”, and it implies that the possibility of bankruptcy is imminent. So, we identify firms in financial distress when they came in the “distress zone”, when they have a Z’ Score less than 1.10 (FIDA). The formula may be used to predict the probability that a firm will go bankrupt within two years. The Z’Score uses multiple corporate income and balance sheet variables to measure the financial health of a company. Z’Score formula given by Altman for manufacturing firms is as follows: Z − Score = 0.717.X 1 + 0.847.X 2 + 3.107.X 3 + 0.420.X 4 + 0.998.X 5 where X1 = (current assets—current liabilities)/total assets, X2 = retained earnings/ total assets, X3 = earnings before interest and taxes/total assets, X4 = book value of equity/total liabilities and X5 = sales/total assets. Financial Distress Ratio (FDB): According to this measure the company is financially distressed when in a given year its EBITDA is lower than the financial expenses (Wruck 1990; Asquith et al. 1994; Andrade and Kaplan 1998; Whitaker 1999; Bhagat et al. 2005; Pindado et al. 2008; Lopez-Gutierrez et al. 2015; Gupta and Mahakud 2022). We consider a firm to be under distress if its financial distress ratio is below 1 in any period. This financial distress ratio is calculated as: Financial Distress Ratio or F D Rit = E B I T D Ait /F E it where EBITDA is Earnings before interest, tax, depreciation and amortization and FE is financial expenses (the amount of interest expenses over debt borrowings). Ohlson’s Bankruptcy Probabilities Method (FIDC): Ohlson (1980) developed Ohlson’s predicted bankruptcy probabilities model to predict the bankruptcy of the U.S. firms. Ohlson’s model is a result of the 9-factor linear combination of coefficient weighed business ratios which can be easily captured by financial statements of companies. According to this model if the probability of bankruptcy is greater than 0.5, the firm is said to be financially distressed. Ohlson’ model is calculated by the probability (P) of bankruptcy and is represented as follows: P=

1 1 + e−yit

yit = −1.32 − 0.407 ∗ S I Z E + 6.03 ∗ T L T A − 1.43 ∗ W C T A + 0.757 ∗ C LC A − 2.37 ∗ N I T A − 1.83 ∗ FU T L + 0.285 ∗ I N T W O − 1.72 ∗ O E N E G − 0.521 C H I N Here, SIZE = log of total assets to GNP price-level index ratio, TLTA = total liabilities to total assets, WCTA = working capital to total assets, CLCA = current liabilities to current assets, NITA = net income to total assets, FUTL = funds from operations to total liabilities, INTWO = one if net income is negative in the previous 2 years

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or zero otherwise, OENEG = one if total liabilities are greater than total assets or zero otherwise, CHIN = (NI t − NI t −1 )/(NI t − NI t −1 ) where NI t is the net income for year t. Considering these models, a firm, which came under financial distress condition considered as a financial distress company and is represented by dummy variables (1) and the firm that does not belong to the financial distress criteria are considered as the healthy firms represented by the dummy (0). This chapter argues that financial distress makes firms more financially constrained due the high cost of borrowing and limited availability of external funds. Therefore, the investment decisions get affected through the channel of investmentcash flow sensitivity, and it is assumed that distress effect increases investment-cash flow sensitivity. This could be due to the fact that a distressed firm faces more borrowing constraints than the non-distressed firms which makes firms to rely more on their internal fund. This chapter also assumes that the effect of distress is less or nil on the investment- cash flow sensitivity for the group affiliated firms, in the non-crisis period and firms having higher Q ratio.

6.3.2 Data The firm specific data is collected from the prowess data base maintained by the Centre for Monitoring the Indian Economy (CMIE). The macroeconomic data used in this study was collected from the Reserve Bank of India. The study period is 1998–1999 to 2013–14. The main reasons to select this time period as a period of study are first, this time period refers to the period of liberalization, privatization and globalization in India and second, during this time period maximum possible information is available for sample companies in the database. The frequency of data is yearly. To construct a balanced panel data set we have excluded those companies, whose data is not available throughout the period. Out of the total 10,248 companies, we find 1922 companies which have continous fixed investment data during the study period i.e. 1998 to 2013–2014. Out of 1922 firms, 1246 firms did not have the adequate data for other major explanatory variables. Further following Jangili and Kumar (2010), we have not considered 18 Private firms as private firms do not disclose their financial statement. Finally, we selected 617 firms which have continued data throughout the period. Since the dependent variable investment is calculated by taking the first difference of the fixed assets, the first year data is not taken into account in the estimation. Further, we divide our whole sample into two sub samples on the basis of financial crisis occurred in the economy. The first sub period is from 1999–2000 to 2006–07 (non- crisis period), and the second sub period is from 2007–08 to 2013–14 (crisis period), which has witnessed many financial crises such as global financial crisis (2007), European sovereign debt crisis (2010) and Russian financial crisis (2014). We also divide the sample on the basis of Tobin’s Q ratio i.e. the companies having Q ratio more than one (high growth companies) and less than one (companies having high growth opportunity or value companies).

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6.3.3 Preliminary Evidence Table 6.1 shows that 17% of group affiliated firms are financially distressed among all the distressed firms in our sample. This implies that largely, the group affiliated firms are not financially distressed in India. Out of total healthy firms around 66 percent are group affiliated. We observe that investment to capital ratio, sales to capital ratio and cash flow to capital ratio are higher for business group affiliated firm than the standalone firms (non-group affiliated firms). The business group affiliated firms pay less cost of borrowing, use more debt and have more growth opportunities in comparison to standalone firms. It could be due to the sharing of the internal capital market, technology, risk, and other facilities among the business group affiliated firms which help them to finance their investment even in the absence of internal fund. Further, it can also be argued that group affiliated firms may have more reputation in the market which help them to decrease their cost of borrowings and enhance the debt capacity, and this effect also affects the sales and cash flow in a positive manner (Table 6.2). Table 6.3 provides summary statistics of all the variables for different types of firms classified on the basis of group affiliation within the financially distressed and healthy firms. We observe that investment to capital ratio, Tobin’s Q ratio, cash flow to capital ratio and sales to capital ratio have been more for the business group affiliated firms than the standalone firms. This could be due to the availability of internal capital among the group firms, which help t in financing the investment during the distress condition. But the ratio of total interest expenses to total borrowings has been higher for standalone firms. The leverage ratio has been more for group affiliated firms than the standalone firms within the financially distressed firms. We find that within the healthy firms’ investment to capital ratio, Tobin’s Q ratio, sales to capital ratio, cash flow to capital ratio and financial leverage ratio have been more for group affiliated firms than the standalone firms. The investment to capital ratio for group affiliated financially distressed firms has been more than the financially distressed standalone firms throughout the study period. This finding is consistent across the three measures used for measuring financial distress (Figs. 6.1, 6.2 and 6.3). Table 6.1 Percentage of financially distressed and healthy firms across group affiliation

FDA

FDB

FDC

(i) Business group affiliated

17

17

18

(ii) Standalone

83

83

82

(i) Business group affiliated

66

63

66

(ii) Standalone

34

37

34

Items Distressed firms (%)

Healthy firms (%)

Note FDA, FDB and FDC represent the different measurement to capture financial distress Source Prowess data base maintained by CMIE

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Table 6.2 Summary statistics of the major variables I /K

Q

S/K

C F/K

T I E/T B

LEV

Mean (std. dev.)

Mean (std. dev.)

Mean (std. dev.)

Mean (std. dev.)

Mean (std. dev.)

Mean (std. dev.)

All firms (618)

0.13 (0.23)

1.27 (0.74)

0.19 (0.46)

0.22 (0.31)

0.12 (0.35)

0.42 (0.68)

Business group affiliated firms (397)

0.17 (0.21)

1.54 (0.79)

0.22 (0.47)

0.24 (0.33)

0.11 (0.39)

0.48 (0.74)

Standalone firms (221)

0.12 (0.26)

0.79 (0.62)

0.18 (0.37)

0.17 (0.38)

0.12 (0.35)

0.40 (0.56)

Type of firms

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, Q = Tobin’s Q ratio, S = sales, C F = cash flow, T I E = total interest expenses, T B = total borrowings, and L E V = leverage. The firms affiliated to a particular group are considered as group affiliated firms and rest are designated as standalone firms Source Prowess data base maintained by CMIE

6.4 Model Specification and Econometric Method 6.4.1 Models Specifications Assuming the role of business group affiliations on determination of corporate investments and investment-cash flow sensitivity we specify the models as follows: (/ ) (/ ) ( / ) I I CF K it = α + β1 K it−1 + β2 Q it + β3 K it ( / ) + β4 C F K × BG Ai + β5 BG Ai + ϑi + λt + μit it

(/ ) (/ ) ( / ) ( / ) I I S CF K it = α + β1 K it−1 + β2 K it + β3 K it ( / ) + β4 C F K × BG Ai + β5 BG Ai + ϑi + λt + μit it

(6.1)

(6.2)

(/ ) (/ ) ( / ) I I S = α + β + β Q + β 1 2 it 3 K it K it−1 K it ( / ) ( ) / + β4 C F K + β5 T I E T B + β6 L I Q it + β7 L E Vit it it ( / ) + β8 S Z it + β9 T ANit + β10 AG E it + β11 C F K it × BG Ai + β12 BG Ai + θi + λt + μit

(6.3)

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Table 6.3 Summary statistics of the variables across the group affiliation (within the distressed and healthy firms) Panel A: distressed firms Variables

FDA

FDB

FDC

Group affiliated firms Mean (SD)

Standalone firms Mean (SD)

group affiliated firms Mean (SD)

Standalone firms Mean (SD)

group affiliated firms Mean (SD)

Standalone firms Mean (SD)

(1)

(2)

(3)

(4)

(5)

(6)

I /K

0.12 (0.21)

0.04 (0.15)

0.10 (0.15)

0.05 (0.18)

0.11 (0.13)

0.07 (0.19)

Q

1.61 (0.87)

1.22 (0.92)

1.81 (0.51)

1.14 (0.71)

1.83 (0.48)

1.09 (0.78)

S/K

0.10 (0.17)

0.07 (0.18)

0.09 (0.11)

0.04 (0.12)

0.07 (0.12)

0.06 (0.14)

C F/K

0.09 (0.19)

0.05 (0.11)

0.06 (0.12)

0.05 (0.17)

0.05 (0.09)

0.04 (0.13)

T I E/T B

0.09 (0.43)

0.13 (0.21)

0.08 (0.21)

0.10 (0.23)

0.09 (0.15)

0.10 (0.18)

LEV

0.51 (0.69)

0.42 (1.02)

0.54 (0.58)

0.51 (0.67)

0.51 (0.53)

0.46 (0.62)

Panel B: healthy firms I /K

0.19 (0.27)

0.09 (0.15)

0.18 (0.18)

0.11 (0.28)

0.19 (0.09)

0.12 (0.21)

Q

1.33 (0.35)

1.06 (0.49)

1.38 (0.33)

1.04 (0.42)

1.31 (0.41)

0.98 (0.42)

S/K

0.18 (0.28)

0.12 (0.31)

0.14 (0.26)

0.10 (0.29)

0.16 (0.18)

0.12 (0.23)

C F/K

0.12 (0.19)

0.09 (0.15)

0.13 (0.18)

0.07 (0.19)

0.14 (0.11)

0.10 (0.17)

T I E/T B

0.08 (0.41)

0.12 (0.21)

0.08 (0.17)

0.10 (0.18)

0.08 (0.14)

0.11 (0.16)

LEV

0.48 (0.61)

0.43 (78)

0.49 (0.32)

0.44 (0.58)

0.45 (0.28)

0.44 (0.33)

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, Q = Tobin’s Q ratio, S = sales, C F = cash flow, T I E = total interest expenses, T B = total borrowings, and L E V = leverage. The firms affiliated to a particular group are considered as group affiliated firms and rest are designated as standalone firms Source Prowess data base maintained by CMIE

J. Mahakud and G. Gupta

15 5

10

(Percent)

20

25

146

2000

2002

2004

2006

2008

2010

2012

2014

(Years) Group Affiliated Firms

Standalone Firms

Fig. 6.1 Investment to capital ratio for financially distressed business group affiliated and standlaone firms (financial distress is measured through Altman’s Z score). Source Prowess data base maintained by CMIE

Here, C F= cash flow, T I E = total interest expenses, T B = total borrowings, L I Q = liquidity, L E V = leverage, S Z = firm size, TAN = collateral assets and, AG E = firm age, BGA = Business group affiliation dummy i.e. 1 for the company which is affiliated to a group and 0 otherwise. ϑi is the firm specific effects, λt is the time specific effect, μit is the error term. The subscripts i and t represent the firms’ and time respectively. We expect the positive association between investment and group affiliation in all models as business group member firms shares their internal capital market, technology and resources which help them to make more investment even in the absence of internal fund and resources. The interaction terms in Eqs. (6.1, 6.2 and 6.3) capture the effect of business group affiliation on the sensitivity of investment to internal funds. We expect that β3 > 0 in Eqs. 6.1 and 6.2 and β4 > 0 in Eq. 6.3 as an increase in cash flow lead to an increase in the level of investment expenditure. The major objective of this investigation is that the sensitivity of investment to cash flow may decrease with the affiliation of the firm with the business group because the business group affiliated firms create an internal capital market and share it in times of limited availability of internal fund to finance their investment and ultimately their investment becomes less dependent on the internal fund. Therefore, we expect that β4 < 0, β4 < 0 and β11 < 0 for the Eqs. 6.1, 6.2 and 6.3 respectively.

147

15 5

10

(Percent)

20

25

6 Business Group Affiliation, Financial Distress and Corporate …

2000

2002

2004

2006

2008

2010

2012

2014

(Years) Group Affiliated Firms

Standalone Firms

Fig. 6.2 Investment to capital ratio for financially distressed business group affiliated and standlaone firms (financial distress is measured through financial distress ratio). Source Prowess data base maintained by CMIE

To investigate the relative importance of group affiliation on financially distressed firms within the group affiliated against the financially distressed standalone firms we specify the following models. (/ ) (/ ) ( / ) ( / ) I I CF CF K it = α + β1 K it−1 + β2 Q it + β3 K it + β4 K it ( / ) × ST AN Di × F Dit + β5 C F K × G R OU Pi × F Dit it + β6 F Dit + β7 BG Ai + θi + λt + μit

(6.4)

(/ ) ( / ) ( / ) ( / ) (/ ) I S CF CF I K it−1 + β2 K it + β3 K it + β4 K it K it = α + β1 ( / ) × ST AN Di × F Dit + β5 C F K × G R OU Pi × F Dit it

+ β6 F Dit + β7 BG Ai + θi + λt + μit (/ ) (/ ) ( / ) I I S K it = α + β1 K it−1 + β2 Q it + β3 K it ( / ) ( ) / + β4 C F K + β5 T I E T B + β6 L I Q it + β7 L E Vit it

it

(6.5)

J. Mahakud and G. Gupta

15 5

10

(Percent)

20

25

148

2000

2005

2010

2015

(Years) Group Affiliated Firms

Standalone Firms

Fig. 6.3 Investment to capital ratio for financially distressed business group affiliated and standlaone firms ( financial distress is measured through Ohlson’s O score). Source Prowess data base maintained by CMIE

( / ) + β8 S Z it + β9 T ANit + β10 AG E it + β11 C F K it ( / ) C F × ST AN Di × F Dit + β12 K it × G R OU Pi × F Dit + β13 F Dit + β14 BG Ai + θi + λt + μit

(6.6)

Here, I = net investment, K = capital stock at the beginning of the period, Q = Qratio, S = net sales, CF is the internal cash flow of the firm, FD is the financial distress proxy measured in three ways (represented as FDA, FDB and FDC discussed in the variable section). T I E = total interest expenses, T B = total borrowings, L I Q = liquidity, L E V = leverage, S Z = firm size, TAN = tangible assets, AG E = firm age, ST AN D is a dummy variable whose value is 1 for standalone companies and zero otherwise. Similarly G R OU P is a dummy whose value is 1 for group affiliated firms and zero otherwise. Here, we assume that companies under financial distress restrict their investment and therefore, we expect that β6 < 0 (for Eqs. 6.4 and 6.5) and β13 < 0 (for Eq. 6.6). Comparing the absolute values of the coefficients β4 and β5 in Eqs. (6.4) and (6.5) and β11 &β12 in Eq. 6.6 we examine the relative impact of financial distress on group affiliated vs. standalone firms. In this context, we hypothesize that the effect of financial distress may have less effect on investment-cash flow sensitivity of business group affiliated firms than standalone firms.

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149

6.4.2 Econometric Method Dynamic panel data models have been used for this analysis. For the dynamic analysis, we have used the Generalized Method of Moments (GMM) technique as suggested by Arellano and Bond (1991). When the dynamic model as specified in all the above-mentioned equations are used, the lagged dependent regressor is correlated with the error term even if the errors themselves are uncorrelated. This renders fixed effect estimators to be biased and inconsistent (for fixed T). The random effect estimator is also biased in this context. Simpler instrumental variable estimators may be used but if the errors are correlated then generalized method of moments (GMM) technique is more appropriate. To examine the validity of the instruments used in the analysis we have used the Sargan (1958) test. The Sargan test statistics follows the chi-square distribution. We have also reported the Wald test which shows the joint significance of the estimated coefficients for all the variables and m 1 and m 2 test statistics to test the relevance of the variables used for the analysis and to test the autocorrelation problem.

6.5 Discussion of Results 6.5.1 Empirical Results (Whole Period) Table 6.4 shows the GMM estimation results of Eqs. 6.1, 6.2 and 6.3. Columns 1, 2 and 3 show the result for the Q-model, Euler equation and extended model respectively. The p-values of m 1 and m 2 test statistics indicate that very little unobserved firm specific effects exist in the estimation results. The results from Sargan test reveal that the instruments used are valid. The Wald test confirms that the models are correctly specified. The significant positive coefficient of lagged investment to capital ratio implies that current investment depends on the past investment (i.e. there has been a persistence effect in firms’ investment undertaken). This positive effect is consistent with the findings in Laeven (2003), Love (2003), Ratti et al. (2008), Firth et al. (2012), Tran and Le (2017) and Gupta and Mahakud (2019, 2020, 2022), but inconsistent with the evidence shown by Guariglia (2008) and Gochoco-Bautista et al. (2014). Tobin’s Q plays the significant role of increasing the investment to capital ratio as predicted by the theory. The significant regression coefficient of sales confirms its strong explanatory power for firm investment determination. The significant positive coefficient of cash flow in all investments models suggests that Indian firms are financially constraint. It is consistent with the findings of Fazzari et al. (1988), Guariglia (2008), Jangili and Kumar (2010) and Gupta and Mahakud (2018, 2019, 2022). The negative and significant relationship between interest expenses and investment is consistent with the neo classical theory of investment which assumes that the high cost of borrowing reduces the corporate fixed investment (Rajakumar 2005; Jangili and

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Table 6.4 Business group affiliation and investment-cash flow sensitivity Variables

Q-model (Eq. 6.1) Euler equation (Eq. 6.2) Extended model (Eq. 6.3) Coefficient (z)

Coefficient (z)

Coefficient (z)

(1)

(2)

(3)

0.0894**

0.0613**

(2.18)

(2.08)

0.1019** (2.38)

0.0938*** (2.85)

–

0.0622*** (7.78)

–

0.1104** (2.05)

0.1022*** (8.67)

0.0911*** (2.99)

0.0807*** (2.69)

0.1227*** (9.3)

–

–

−0.0201* (-2.10)

L I Q it

–

–

0.0433*** (4.28)

L E Vit

–

–

−0.0175* (-1.77)

S Z it

–

–

0.1437*** (4.85)

T ANit

–

–

0.0543*** (4.14)

AG E it

–

–

0.1002* (1.82)

-0.0391 (−1.09)

−0.0872 (−1.27)

(/ ) I K it−1 Qit ( / ) S K it ( / ) CF K it ( ) / TIE T B it

( / ) CF −0.0429 K it × BG Ait (−1.10) BG Ait

0.0716** (2.11)

0.0851** (2.38)

0.0982*** (3.30)

Constant

0.0028* (1.81)

0.0303** (2.45)

0.0219*** (2.66)

Wald test

χ2 (06) = 671.16 (0.0000)

χ2 (06) = 658.33 (0.0000)

χ2 (13) = 823.28 (0.0000)

m 1 (p)

(0.00)

(0.00)

(0.00)

m 2 (p)

(0.19)

(0.29)

(0.27) (continued)

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151

Table 6.4 (continued) Variables

Q-model (Eq. 6.1) Euler equation (Eq. 6.2) Extended model (Eq. 6.3) Coefficient (z)

Coefficient (z)

Coefficient (z)

(1)

(2)

(3)

Sargan test

χ2

(90) = 19.18 (0.1203)

χ2

(90) = 21.51 (0.1103)

χ2 (90) = 16.74 (0.1514)

NOB

8021

8021

8021

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, C F = cash flow, S = sales, T I E = total interest expenses, T B = total borrowings, Q = Tobin’s Q ratio, L I Q = liquidity, L E V = leverage, S Z = firm size and, AG E = firm age, BG A= business group affiliation, i = number of firms represented as 1, 2,…,n, and t = time period. (ii) ***, ** and * show the 1%, 5% and 10% level of significance respectively. (iii) z-statistics given in the parenthesis. (iv) m 1 (m 2 ) is a test for first- (second-) order serial correlation in the first-differenced residuals, asymptotically distributed as N(0,1) under the null of no serial correlation. (v) Wald test is a test of joint significance of the estimated coefficients which is asymptotically distributed as chi-square under the null of no relationship and Sargan test of over identifying restrictions, which is asymptotically distributed as chi-square under the null of instrumental validity. (vi) NOB is the number of observations

Kumar 2010; La Cava et al. 2005; Gupta et al. 2018 and Gupta and Mahakud 2022). The regression coefficient of liquidity is positive and statistically significant, which implies that liquid assets do explain the investment behavior of the firms. A negative influence of leverage on investments postulates that external financing through debt leads to the certain fixed obligations for firms such as the payment of interest and principal. Further, if firms fail to pay interest and principle amount that can increases the bankruptcy and liquidation cost and high use of debt or high leverage increases probability of financial distress which in turn reduces the corporate investment (Hiller et al. 2010; Lang et al. 1996, Aivazian et al. 2005, Gupta and Mahakud 2018). The regression coefficient of firm size is positive and significant. This result supports the argument that the cost of capital is lesser for the large companies due to the less asymmetric information problem. Tangibility has also positive impact on the investment decision of the companies. The positive impact of firm age is consistent with the argument that matured and old firms are reputed and have strong social network which helps in obtaining capital from the market, and therefore, they can invest more. The signs of the regression coefficients of interaction term of cash flow with business group dummy have been negative in all models. This implies that investment behavior of group affiliated companies is the less sensitive to the cash flow. This could be because of the availability of internal capital market and a better reputation for the group affiliated companies. The positive and statistically significant value of the business group dummy reveals that corporate fixed investment increases with the affiliations of firms with a business group. It could be due to the fact that business group firms have their own internal capital market which helps member firms to finance their investment in the absence of internal fund.

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Table 6.5 reveals that the regression coefficient of the interaction terms of cash flow, group affiliation and financial distress is negative, but not statistically significant for the business group affiliated firms, which implies that financial distress does not affect the investment-cash flow sensitivity of the affiliated firms in India. This could be due to the fact that business groups might be able to fulfill the financing requirements through the internal capital market. This result also suggests that the effects of group affiliation dominate the effect of financial distress on the investment cash-flow sensitivity. For standalone firms it has been positive and statistically significant. This finding is consistent with the argument that it may be more difficult for the financially distressed standalone firms to raise the external capital and therefore, these firms rely more on the cash flow for the investments in fixed assets. The results indicate that financial distress plays a negative role in the determination of corporate investment. This could be due to the fact that a financial distress firms are facing constraints to finance their investment. Internal financing becomes a constraints for a firm which is under the distress condition because distress firms need to pay their old debt as well as finance their project form the internal fund. External financing also becomes a constraint because lenders are aware about their current situation and feel that it will be riskier to provide more loans to a firm which is already in default to repay their old loan and interest.

6.5.2 Empirical Results (Crisis vs. Non-crisis Periods) Tables 6.6 and 6.7 show the results of the crisis and non-crisis period respectively. We find that variables like firm age and liquidity turnout to be significant during the crisis period. High coefficient values of all firm specific variables reveal that the impact of all these firm specific variables is more on investment decisions during the crisis period that non-crisis period. The negative coefficients of the interaction terms of cash flow, financial distress and group affiliation in both periods depict that the presence of financial distress does not affect the investment-cash flow sensitivity of group-affiliated firms. We find that that there is a difference between the coefficients of interaction term across the periods. High coefficients of interaction term in noncrisis period postulates that business group might have more impact on cash-flow investment sensitivity in the non-crisis period that the crisis period. The results of the interaction terms of cash flow, financial distress and standalone dummy conclude that financial distress does affect the investment-cash flow sensitivity of standalone firms. Our results also report that the isolated effect of financial distress on corporate investment is more during the crisis period than the non-crisis period. Further, the impact of business group affiliation is more on the corporate investment during the non-crisis period than the crisis period.

–

–

–

–

L E Vit

S Z it

T ANit

AG E it

–

–

–

–

–

–

–

–

0.0712** (2.49)

0.0879** (2.33)

–

–

–

–

–

–

0.0501** (2.11)

–

–

–

–

–

–

–

0.1112** (2.38)

0.1095** (2.63)

–

–

–

–

–

–

0.0612** (2.45)

0.1312** (2.45)

–

–

–

–

–

–

–

0.0623** (2.18)

0.1012** (2.45)

–

0.0817*** (7.48) 0.0749 (1.65)

0.0874*** (6.25) 0.0642*** (2.68)

0.0815 (1.33)

−0.1149*** −0.0918 (−2.56) (−1.38)

−0.1047** (−2.33)

0.0767 (1.45)

0.0841 (1.19)

0.0826** (2.42)

(continued)

0.0813** (2.46)

0.0624 (1.16)

0.0916*** (4.55)

0.0831 (1.44)

−0.0955 (−1.27)

−0.0916** (−2.28)

−0.0806 (−1.24)

0.0642** (2.45)

0.0911** (2.41)

0.0944 (1.37)

0.0887** (2.35)

0.0841* (1.94)

0.0849 (1.14)

0.0959** (2.14)

0.0708 (1.46)

0.0626** (2.33)

0.1044* (1.80)

–

–

0.0954* (1.68)

–

0.0995* (1.91)

0.1411* (1.88)

0.1195* (1.88)

0.1132* (1.72)

0.1059* (1.79)

0.0911** (2.21)

0.1187* (1.78)

0.1056* (1.91)

0.1311** (2.43)

0.1211* (1.88)

Extended model with financial distress Coefficient (z)

Euler equation with Financial Distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

L I Q it

( / ) CF K it ( ) T I E/ T B it

( / ) S K it

Qit

(/ ) I K it−1

Variables

Table 6.5 Business group affiliation, financial distress and investment-cash flow sensitivity

6 Business Group Affiliation, Financial Distress and Corporate … 153

– –

– –

– – −0.0618 (−1.47) – – −0.0947* (−1.68)

– −0.0432 (−1.52) – – −0.0612* (−1.67) – 0.1158** (2.35)

–

–

−0.0415* (−1.85)

–

–

0.0921** (2.37)

F D Ait

F D Bit

F DCit

BGAi

0.1016** (2.38)

0.1236** (2.41)

−0.0318* (−1.91)

−0.0392 (−1.48)

–

−0.0821 (−1.39)

0.2418** (2.27)

–

–

( / ) CF K it × F DCit × ST AN Dit ( / ) CF K it × F D Ait × G R OU Pit ( / ) CF K it × F D Bit × G R OU Pit ( / ) CF K it × F DCit × G R OU Pit

–

0.2425* (1.78)

0.2227** (2.02) –

–

0.0813** (2.26)

–

−0.0811* (−1.82)

–

–

−0.0361 (−1.41)

–

–

0.2611** (2.23)

–

0.1123** (2.44)

−0.0740** (−2.21)

–

–

−0.0521 (−1.13)

–

–

0.2128** (2.13)

–

–

0.1248** (2.34)

–

–

−0.0484* (−1.72)

–

–

−0.0511 (−1.31)

–

–

0.2241*** (2.88)

0.1055** (2.47)

–

−0.0422* (−1.62)

–

–

−0.0583 (−1.38)

–

–

0.2446** (1.99)

–

(continued)

0.1156** (2.39)

−0.0831* (−1.93)

–

–

−0.0611 (−1.59)

–

–

0.2642*** (2.56)

–

–

–

0.2503** (1.99)

Extended model with financial distress Coefficient (z)

Euler equation with Financial Distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

–

( / ) CF K it × F D Bit × ST AN Dit

( / ) CF K it × F D Ait × ST AN Dit

Variables

Table 6.5 (continued)

154 J. Mahakud and G. Gupta

Euler equation with Financial Distress

χ2 (6) = 119.10 (0.0000) (0.00) (0.26) 7371

χ2 (6) = 219.80 (0.0000)

(0.00)

(0.30)

(0.21)

7371

Wald test

m 1 (p)

m 2 (p)

Sargan test 6188

(0.19)

(0.18)

(0.00)

χ2 (6) = 196.11 (0.0000)

−0.1129 (−1.26)

7371

(0.16)

(0.17)

(0.00)

χ2 (6) = 217.62 (0.0000)

0.0921 (1.23)

7371

(0.11)

(0.27)

(0.00)

χ2 (6) = 217.62 (0.0000)

0.1092*** (2.66)

6188

(0.17)

(0.26)

(0.00)

χ2 (6) = 217.62 (0.0000)

0.1411** (2.16)

7371

(0.23)

(0.19)

(0.00)

χ2 (13) = 428.26 (0.0000)

0.1024* (1.91)

7371

(0.18)

(0.24)

(0.00)

χ2 (13) = 385.12 (0.0000)

0.0846 (1.61)

6188

(0.19)

(0.23)

(0.00)

χ2 (13) = 426.21 (0.0000)

0.1216* (1.67)

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, C F = cash flow, S = sales, Q = Tobin’s Q ratio, T I E = total interest expenses, T B = total borrowings, Q = Tobin’s Q ratio, L I Q = liquidity, L E V = leverage, S Z = firm size, T AN = tangible assets, and AG E = firm age, i = number of firms represented as 1, 2,…,n, and t = time period. (ii) ***, ** and * show the 1%, 5% and 10% level of significance respectively. (iii) z-statistics given in the parenthesis. (iv) m 1 (m 2 ) is a test for first- (second-) order serial correlation in the first-differenced residuals, asymptotically distributed as N(0,1) under the null of no serial correlation. (v) Wald test is a test of joint significance of the estimated coefficients which is asymptotically distributed as chi-square under the null of no relationship and Sargan test of over identifying restrictions, which is asymptotically distributed as chi-square under the null of instrumental validity. (vi) NOB is the number of observations. (vii) F D A, F D B, and F DC considered as financial distress measurement by Altman’s Z”-Score model, financial distress ratio, and Ohlson’s O score model respectively

(0.28)

0.1021** (2.16)

0.1211 (1.18)

Coefficient (z)

Extended model with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

Constant

Variables

Table 6.5 (continued)

6 Business Group Affiliation, Financial Distress and Corporate … 155

–

–

–

–

LEV it

SZ it

TAN it

AGE it

–

–

–

–

–

–

–

–

– 0.1507** (2.41)

0.1426** (2.14)

0.1581** (2.33)

0.1754** (2.45)

0.0852 (1.22)

0.0626 (1.13)

–

) T I E/ T B it

Euler equation with financial distress

Extended model with financial distress

–

–

–

–

–

–

0.1841** (2.34)

–

0.1154* (1.84)

0.0846 (1.19)

–

–

–

–

–

–

0.1952** (2.48)

0.1812** (2.81)

–

0.0561 (1.27)

–

–

–

–

–

–

0.1954** (2.49)

0.1742** (2.51)

–

0.0811 (1.16)

-

–

–

–

–

–

0.1628** (2.34)

0.1901** (2.44)

–

0.0411 (1.18)

0.1851** (2.31) −0.1054** (-2.41) 0.0941** (2.19) −0.1245** (-2.44) 0.1051*** (8.47) 0.0847** (2.16) 0.0715* (1.72)

−0.1243** (-2.29) 0.1188** (2.33) −0.1483** (-2.39) 0.0971*** (4.29) 0.0811** (2.33) 0.0767* (1.65)

0.2108** (2.39)

0.0849 (1.14)

0.0381 (1.35)

0.1911** (2.44)

0.1768** (2.36)

0.0626** (2.33)

0.0543 (1.47)

(continued)

0.0851* (1.86)

0.0751** (2.19)

0.1158*** (9.33)

−0.1135** (-2.31)

0.0857* (1.64)

−0.0958** (-2.33)

0.1649** (2.29)

0.1956** (2.54)

0.0944 (1.37)

0.0419 (1.41)

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

LIQit

(

( / ) CF K it

( / ) S K it

Qit

(/ ) I K it−1

Variables

Table 6.6 Business group affiliation, financial distress and investment-cash flow sensitivity (crisis period)

156 J. Mahakud and G. Gupta

Euler equation with financial distress

Extended model with financial distress

– –

– – −0.0988** (−2.18)

– −0.0914** (−2.36) – 0.0914** (2.18)

−0.1124** (−2.23)

–

–

0.0729** (2.38)

F D Ait

F D Bit

F DCit

BGAi

0.0748** (2.29)

–

−0.0614 (−1.25)

–

–

0.1144** (2.13)

−0.1247** (−2.49)

–

–

−0.0533 (-1.27)

–

−0.0439 (-1.24)

–

0.1914** (2.33) –

–

–

–

0.2214* (1.89)

–

–

–

0.1922** (2.23)

–

–

0.2347** (2.12)

0.0907* (1.88)

–

−0.1173** (−2.33)

–

–

−0.0416 (-1.23)

–

–

0.2147** (2.41)

–

0.0733** (2.46)

−0.1048** (-2.47)

–

–

−0.0519 (-1.24)

–

–

0.1846** (2.17)

–

–

0.0774** (2.09)

–

–

−0.1431** (-2.11)

–

–

-0.0522 (-1.27)

–

–

0.1931** (2.38)

–

−0.0483 (-1.29)

–

–

0.1844** (2.36)

–

–

0.0817* (1.86)

–

(continued)

0.0915** (1.99)

−0.1183** (-2.39)

−0.1136** – (-2.19)

–

–

−0.0509 (-1.14)

–

–

0.2041** (2.11)

–

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

−0.0722 (-1.17)

( / ) CF K it × F D Ait × G R OU Pit ( / ) CF K it × F D Bit × G R OU Pit ( / ) CF K it × F DCit × G R OU Pit

it

( / ) CF K it × F D Bit × ST AN Dit ( / ) CF × F DCit × ST AN Dit K

( / ) CF K it × F D Ait × ST AN Dit

Variables

Table 6.6 (continued)

6 Business Group Affiliation, Financial Distress and Corporate … 157

Euler equation with financial distress

Extended model with financial distress

(0.32) 2835

2380

(0.31)

(0.21)

(0.00)

χ2 (8) = 496.18 (0.0000)

−0.0744 (−1.28)

2835

(0.33)

(0.29)

(0.00)

χ2 (8) = 318.22 (0.0000)

0.0927 (1.43)

2835

(0.29)

(0.25)

(0.00)

χ2 (8) = 358.11 (0.0000)

0.0792* (1.68)

2380

(0.28)

(0.27)

(0.00)

χ2 (8) = 422.15 (0.0000)

0.0527* (1.76)

2835

(0.29)

(0.22)

(0.00)

χ2 (15) = 325.18 (0.0000)

0.0731* (1.79)

2835

(0.24)

(0.23)

(0.00)

χ2 (15) = 386.11 (0.0000)

0.0342 (1.36)

2380

(0.21)

(0.24)

(0.00)

χ2 (15) = 488.17 (0.0000)

0.0215* (1.77)

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, C F = cash flow, S = sales, Q = Tobin’s Q ratio, T I E = total interest expenses, T B = total borrowings, Q = Tobin’s Q ratio, L I Q = liquidity, L E V = leverage, S Z = firm size, T AN = tangible assets, and AG E = firm age, i = number of firms represented as 1, 2,…,n, and t = time period. (ii) ***, ** and * show the 1%, 5% and 10% level of significance respectively. (iii) z-statistics given in the parenthesis. (iv) m 1 (m 2 ) is a test for first- (second-) order serial correlation in the first-differenced residuals, asymptotically distributed as N(0,1) under the null of no serial correlation. (v) Wald test is a test of joint significance of the estimated coefficients which is asymptotically distributed as chi-square under the null of no relationship and Sargan test of over identifying restrictions, which is asymptotically distributed as chi-square under the null of instrumental validity. (vi) NOB is the number of observations. (vii) F D A, F D B, and F DC considered as financial distress measurement by Altman’s Z”-Score model, financial distress ratio, and Ohlson’s O score model respectively

(0.35)

2835

Sargan test

NOB

(0.26)

(0.00)

(0.00)

(0.32)

m 1 (p)

χ2 (8) = 319.17 (0.0000)

χ2 (8) = 417.28 (0.0000)

Wald test

m 2 (p)

0.0621* (1.69)

0.0511 (1.19)

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

Constant

Variables

Table 6.6 (continued)

158 J. Mahakud and G. Gupta

–

–

TAN it

AGE it

0.16267* (1.88)

–

–

–

SZ it

0.1108** (2.33)

0.1328** (2.14)

–

–

–

LEV it

0.0754** (2.33)

0.0924** (2.14)

–

–

–

–

–

–

0.0746* (1.79)

0.0824* (1.74)

–

( / ) CF K it × F D Ait × ST AN Dit

Euler equation with financial distress

Extended model with financial distress

–

–

–

–

–

–

–

0.1173** (2.38)

–

0.0474** (1.97)

0.0833* (1.84)

0.1429* (1.74)

–

–

–

–

–

–

0.1419** (2.51)

0.1118** (2.38)

–

0.0713* (1.67)

–

–

–

–

–

–

–

0.1341** (2.44)

0.0944** (2.27)

–

0.0735* (1.94)

-

–

–

–

–

–

–

0.1138** (2.11)

0.0788** (2.47)

–

0.0766* (1.89)

0.0844** (2.48) 0.0619** (2.08)

0.0874** (2.21) 0.0610** (2.14)

0.1413* (1.68)

–

0.0644 (1.22)

−0.0693** (−2.07)

−0.0829** (−2.17)

0.0531 (1.16)

0.0433 (1.19)

−0.0644** (−2.16)

−0.0715** (−2.11) 0.0421 (1.14)

0.1182** (2.05)

0.0842** (2.19)

0.0546* (1.74)

0.0589* (1.81)

0.1247** (2.31)

0.0906** (2.16)

0.0477** (2.31)

0.0614* (1.77)

(continued)

–

0.0671 (1.36)

0.0533** (2.14)

0.0917** (2.09)

−0.0612** (−2.11)

0.0521 (1.18)

−0.0710* (−1.88)

0.1044** (2.13)

0.0813** (2.34)

0.0832* (1.87)

0.0921* (1.88)

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

LIQit

( / ) S K it ( / ) CF K it ( ) T I E/ T B it

Qit

(/ ) I K it−1

Variables

Table 6.7 Business group affiliation, financial distress and investment-cash flow sensitivity (non-crisis period)

6 Business Group Affiliation, Financial Distress and Corporate … 159

it

Euler equation with financial distress

– –

– –

– – −0.0507* (−1.75) 0.1243** (2.41) 0.0736 (1.29)

– −0.1194 (−1.48) − – −0.0702* (−1.86) – 0.1424** (2.31) 0.0428* (1.68)

−0.0951 (−1.27)

–

−

−0.0624* (−1.79)

–

–

0.1134** (2.49)

0.0321 (1.17)

FDAit

FDBit

FDC it

BGAi

Constant

−0.1039 (−1.35)

0.055 (1.23)

0.1508** (2.33)

−0.0613* (−1.71)

–

–

−0.1119 (−1.28)

–

0.1544* (1.73)

–

–

–

–

0.1524* (1.83)

( / ) CF K it × F DCit × G R OU Pit

Extended model with financial distress

0.0741* (1.71)

0.1243** (1.97)

–

−0.0821* (−1.73)

–

–

−0.1287 (−1.33)

–

–

0.1628* (1.93)

0.0531* (1.81)

0.1126** (2.51)

−0.0606* (−1.87)

–

–

−0.0973 (−1.34)

–

–

0.1547* (1.81)

–

0.0784* (1.85)

0.1044** (2.29)

–

–

−0.0519* (−1.69)

–

–

−0.1124 (−1.38)

–

–

0.0426 (1.19)

0.1156** (2.36)

–

−0.0613* (−1.89)

–

–

−0.0943 (−1.19)

–

–

0.1506* (1.71)

(continued)

0.0411* (1.71)

0.1423** (2.47)

−0.0716* (−1.73)

–

–

−0.1159 (−1.31)

–

–

0.1517* (1.85)

–

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

–

( / ) CF K it × F D Bit × ST AN Dit ( / ) CF K it × F DCit × ST AN Dit ( / ) CF K it × F D Ait × G R OU Pit ( / ) CF × F D Bit × G R OU Pit K

Variables

Table 6.7 (continued)

160 J. Mahakud and G. Gupta

Euler equation with financial distress

Extended model with financial distress

(0.34) 3402

2856

(0.33)

(0.24)

(0.00)

χ2 (8) = 448.11 (0.0000)

3402

(0.34)

(0.31)

(0.00)

χ2 (8) = 569.57 (0.0000)

3402

(0.27)

(0.28)

(0.00)

χ2 (8) = 411.87 (0.0000)

2856

(0.25)

(0.29)

(0.00)

χ2 (8) = 429.15 (0.0000)

3402

(0.28)

(0.24)

(0.00)

χ2 (15) = 611.38 (0.0000)

3402

(0.26)

(0.25)

(0.00)

χ2 (15) = 441.51 (0.0000)

2856

(0.29)

(0.26)

(0.00)

χ2 (15) = 511.67 (0.0000)

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, C F = cash flow, S = sales, Q = Tobin’s Q ratio, T I E = total interest expenses, T B = total borrowings, Q = Tobin’s Q ratio, L I Q = liquidity, L E V = leverage, S Z = firm size, T AN = tangible assets, and AG E = firm age, i = number of firms represented as 1, 2,…,n, and t = time period. (ii) ***, ** and * show the 1%, 5% and 10% level of significance respectively. (iii) z-statistics given in the parenthesis. (iv) m 1 (m 2 ) is a test for first- (second-) order serial correlation in the first-differenced residuals, asymptotically distributed as N(0,1) under the null of no serial correlation. (v) Wald test is a test of joint significance of the estimated coefficients which is asymptotically distributed as chi-square under the null of no relationship and Sargan test of over identifying restrictions, which is asymptotically distributed as chi-square under the null of instrumental validity. (vi) NOB is the number of observations. (vii) F I D A, F I D B, and F I DC considered as financial distress measurement by Altman’s Z”-Score model, financial distress ratio, and Ohlson’s O score model respectively

(0.33)

3402

Sargan test

NOB

(0.29)

(0.00)

(0.00)

(0.35)

m 1 (p)

χ2 (8) = 427.15 (0.0000)

χ2 (8) = 528.33 (0.0000)

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

m 2 (p)

Wald test

Variables

Table 6.7 (continued)

6 Business Group Affiliation, Financial Distress and Corporate … 161

162

J. Mahakud and G. Gupta

6.5.3 Empirical Results (High Growth vs. Low Growth Companies) Tables 6.8 and 6.9 show that the presence of financial distress does not affect the investment-cash flow sensitivity of group-affiliated firms for both types of firms classified on the basis of Tobin’s Q ratio. We also find that that there is a difference between the coefficients of interaction terms across the firms. High value of the coefficients of interaction terms of high growth firms postulate that business group might be more helpful to these firms to finance their investment opportunities in terms of providing internal funds. For standalone firms, the impact of financial distress on cash flow sensitivity is highly significant in both the cases. Further we find that the individual effect of financial distress on corporate investment is more for the firms having lower Q ratio. Further, the impact of business group affiliation is more on the corporate investment for the firms with high growth opportunity than the firms with low growth opportunities.

6.6 Conclusions Investment to capital ratio, sales to capital ratio and cash flow to capital ratio are higher for business group affiliated firm than the standalone firms. We find that within the healthy firms’ investment to capital ratio, Tobin’s Q ratio, sales to capital ratio, cash flow to capital ratio and financial leverage ratio have been more for group affiliated firms than the standalone firms. The econometric analysis concludes that there has been a persistence effect in firms’ investment undertaken. The positive impact of cash flow on investment decisions implies that Indian firms are financially constrained. The investment behavior of group affiliated companies is the less sensitive to the cash flow and corporate fixed investment increases with the affiliations of the firm with a business group. It could be due to the fact that business group firms have their own internal capital market which helps member firms to finance their investment in the absence of internal fund. The result reveals that financial distress plays a negative role in the determination of corporate investment. We also find that financial distress does not affect the investment-cash flow sensitivity of the affiliated firms in India. The results are robust across the different periods classified on the basis of financial crisis and growth opportunity of the companies.

–

AGE it

–

–

–

–

SZ it

TAN it T AN it

–

–

LEV it

–

–

–

–

0.07119** (2.42)

0.06179** (2.22)

0.0879** (2.35)

–

–

–

–

–

–

–

–

–

–

0.0732* (1.69)

0.0800* (1.65)

–

–

–

–

–

-

0.0612 (1.12)

0.1010* (1.83)

–

–

–

–

–

–

–

0.0681**\ (2.12)

0.1210* (1.65)

−0.0721 (−1.34) 0.0927 (1.19)

−0.0710 (−1.29) 0.0826** (2.05)

0.0834 (1.61)

0.0751 (1.28)

0.0916 (1.61)

(continued)

0.0716 (1.21)

0.0932* (1.89)

0.0786*** (3.55) 0.0814 (1.17)

0.0872*** (2.88)

−0.0819 (−1.19)

0.0747 (1.15)

−0.0781** (−2.51)

0.0826 (1.23)

0.1523*** (4.04)

0.0841 (1.50)

0.1014* (1.91)

−0.1140*** −0.1094* (−3.55) (−1.81)

0.05621** (2.21)

0.0817*** (2.95)

0.0710 (1.42)

0.0924** (2.24)

0.0721*** (3.01)

0.0611** (2.18)

0.0911 (1.24)

(9)

–

–

0.1019 (1.38)

0.1114** (2.41)

–

0.0968*** (2.74)

0.1191*** (3.51)

(7)

0.0768*** (2.94)

0.1091 (1.56)

(6)

0.0568*** (2.84)

0.0991*** (2.87)

(5)

(8)

0.1031*** (2.64)

(4)

0.1133 (1.54)

0.1033*** (3.14)

(3)

(2)

(1)

Extended model with financial distress Coefficient Coefficient (z) (z)

Euler equation with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

LIQit

( / ) S K it ( / ) CF K it ( ) / TIE T B it

Qit

(/ ) I K it−1

Variables

Table 6.8 Business group affiliation, financial distress and investment-cash flow sensitivity (firms with Q ratio > 1)

6 Business Group Affiliation, Financial Distress and Corporate … 163

it

Euler equation with financial distress

–

−0.0727* (−1.71)

–

−0.0915 (−1.14)

–

–

FDBit

–

–

−0.0931 (−1.27)

–

–

–

–

–

−0.0829 (−1.17)

–

–

0.1722** (2.41)

–

–

−0.0527* (−1.89)

–

–

0.1506** (1.99)

–

–

−0.0468* (−1.92)

−0.1026 (−1.39)

0.1629* (1.69)

(4)

–

–

0.1814** (1.94)

(3)

(2)

(1)

−0.0614* (−1.87)

–

–

−0.0911 (−1.56)

–

–

0.1701** (2.11)

–

(5)

–

–

−0.0814 (−1.18)

–

–

0.1713** (2.44)

–

–

(6)

–

−0.0516* (−1.68)

–

–

−0.0913 (−1.11)

–

–

0.1714** (2.17)

(7)

−0.0566* (−1.73)

–

–

-0.0823 (-1.27)

–

–

0.1641** (1.99)

–

(8)

(continued)

–

–

−0.0953 (−1.21)

-

–

0.1809** (2.15)

–

–

(9)

Coefficient Coefficient (z) (z)

Extended model with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

FDAit

( / ) CF K it × F D Ait × ST AN Dit ( / ) CF K it × F D Bit × ST AN Dit ( / ) CF K it × F DCit × ST AN Dit ( / ) CF K it × F D Ait × G R OU Pit ( / ) CF K it × F D Bit × G R OU Pit ( / ) CF × F DCit × G R OU Pit K

Variables

Table 6.8 (continued)

164 J. Mahakud and G. Gupta

Euler equation with financial distress

0.0681* (1.85)

0.0429* (1.76) χ2 (8) = 189.15 (0.0000) (0.00) (0.20) (0.35) 2158

0.0281 (1.27)

χ2 (8) = 223.13 (0.0000)

(0.00)

(0.19)

(0.33)

2158

Constant

Wald test

m 1 (p)

m 2 (p)

Sargan test

NOB

2158

(0.33)

(0.22)

(0.00)

χ2 (8) = 219.14 (0.0000)

0.0625* (1.71)

0.1044** (2.10)

2158

(0.30)

(0.21)

(0.00)

χ2 (8) = 191.21 (0.0000)

0.0925 (1.30)

0.0813** (1.95)

–

(5)

1820

(0.31)

(0.20)

(0.00)

χ2 (8) = 215.91 (0.0000)

0.0321* (1.89)

0.0957** (2.34)

−0.0622** (−2.14)

(6)

2158

(0.35)

(0.28)

(0.00)

χ2 (15) = 338.19 (0.0000)

0.0329* (1.91)

0.0815** (2.12)

–

(7)

2158

(0.32)

(0.31)

(0.00)

χ2 (15) = 389.21 (0.0000)

0.0671* (1.81)

0.0956** (2.15)

–

(8)

1820

(0.37)

(0.23)

(0.00)

χ2 (15) = 428.14 (0.0000)

0.0529* (1.72)

0.0811** (2.44)

−0.0716* (−1.83)

(9)

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, C F = cash flow, S = sales, Q = Tobin’s Q ratio, T I E = total interest expenses, T B = total borrowings, Q = Tobin’s Q ratio, L I Q = liquidity, L E V = leverage, S Z = firm size, T AN = tangible assets, and AG E = firm age, i = number of firms represented as 1, 2,…,n, and t = time period. (ii) ***, ** and * show the 1%, 5% and 10% level of significance respectively. (iii) z-statistics given in the parenthesis. (iv) m 1 (m 2 ) is a test for first- (second-) order serial correlation in the first-differenced residuals, asymptotically distributed as N(0,1) under the null of no serial correlation. (v) Wald test is a test of joint significance of the estimated coefficients which is asymptotically distributed as chi-square under the null of no relationship and Sargan test of over identifying restrictions, which is asymptotically distributed as chi-square under the null of instrumental validity. (vi) NOB is the number of observations. (vii) F I D A, F I D B, and F I DC considered as financial distress measurement by Altman’s Z”-Score model, financial distress ratio, and Ohlson’s O score model respectively

1820

(0.34)

(0.22)

(0.00)

χ2 (8) = 218.89 (0.0000)

0.1028** (2.31)

0.1126** (2.19)

0.0912** (2.11)

–

−0.0825* (−1.79)

BGit

(4)

(3)

–

(2)

–

(1)

Coefficient Coefficient (z) (z)

Extended model with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

FDC it

Variables

Table 6.8 (continued)

6 Business Group Affiliation, Financial Distress and Corporate … 165

–

–

–

–

SZ it S Z it

TAN it T AN it

AGE it –

–

–

–

–

–

LEV it

0.2297*** (2.68)

0.2297** (2.44)

–

–

–

–

0.1502*** (3.61)

0.1002*** (2.66)

0.2197** (2.45)

–

0.1802*** (2.94)

0.1138 (1.45)

(3)

–

–

–

–

–

–

0.2318** (2.48)

0.1007* (1.77)

–

0.0706* (1.69)

(4)

–

–

–

–

–

–

0.2318** (2.31)

0.1007* (1.81)

–

0.1006* (1.74)

(5)

–

–

–

–

–

–

0.2212** (2.47)

0.1507** (2.19)

–

0.0902 (1.29)

(6)

−0.0874** (−2.21) 0.1014 (1.01)

−0.0910** (−2.23) 0.1114** (2.51)

0.1002** (1.99)

−0.0914 (−1.28)

0.2511*** (3.11)

0.1211 (1.01)

0.1079** (2.15)

0.1201 (1.11)

(9)

Coefficient (z)

0.0814 (1.54) 0.0911*** (2.84)

0.0928*** (2.61)

0.1107 (1.61) 0.0851 (2.19)

0.1108*** (4.06)

(continued)

0.0914* (1.69)

0.0954*** (2.59)

0.1017*** (2.69)

−0.1271*** −0.1108*** −0.1119 (−3.23) (−2.98) (−1.21)

0.2511*** (5.11)

0.0971*** (3.21)

0.0849 (1.31)

0.1144** (2.41)

0.2426*** (5.21)

0.0915*** (3.08)

0.0814** (2.41)

0.1248** (2.51)

(7)

(8)

(2) 0.1128*** (3.49)

(1)

0.1028*** (3.45)

Coefficient (z)

Euler equation with financial distress Extended model with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

LIQit

( / ) S K it ( / ) CF K it ( ) / TIE T B it

Qit

(/ ) I K it−1

Variables

Table 6.9 Business group affiliation, financial distress and investment-cash flow sensitivity (firms with Q ratio < 1)

166 J. Mahakud and G. Gupta

it

FDBit

FDAit

( / ) CF K it × F D Ait × ST AN Dit ( / ) CF K it × F D Bit × ST AN Dit ( / ) CF K it × F DCit × ST AN Dit ( / ) CF K it × F D Ait × G R OU Pit ( / ) CF K it × F D Bit × G R OU Pit ( / ) CF × F DCit × G R OU Pit K

Variables

Table 6.9 (continued)

– –

– – −0.0291 (−1.11)

– −0.0361 (−1.12) –

−0.0414 (−1.11)

–

–

–

−0.0921** – (−2.33)

–

–

0.2900*** (2.82)

–

–

−0.1056** – (−2.27)

–

–

0.3161*** (2.72)

–

–

−0.0922* (−1.92)

−0.0316 (−1.33)

0.2551*** (3.33)

(4)

–

–

(3)

(2)

(1)

0.2722*** (3.89)

−0.1027* (−1.99)

–

–

−0.0305 (−1.61)

–

–

0.3105* (1.65)

–

(5)

–

–

−0.0498 (−1.17)

–

–

0.2498* (1.77)

–

–

(6)

–

−0.0826** (−2.33)

–

–

−0.0241 (−1.15)

–

–

0.2859*** (3.54)

(7)

−0.0914** (−2.41)

–

–

−0.0419 (−1.11)

–

–

0.2911** (1.99)

–

(8)

Coefficient (z)

(continued)

–

–

−0.0359 (−1.26)

–

–

0.2912** (2.09)

–

–

(9)

Coefficient (z)

Euler equation with financial distress Extended model with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

6 Business Group Affiliation, Financial Distress and Corporate … 167

(0.19) 3640

(0.29)

3640

Sargan test

NOB

(4)

3445

(0.26)

(0.20)

(0.00)

χ2 (8) = 211.16 (0.0000)

0.0611 (1.19)

0.0951** (2.34)

3640

(0.18)

(0.18)

(0.00)

χ2 (8) = 427.84 (0.0000)

0.0743* (1.91)

0.1218** (2.19)

−0.1138** – (−1.98)

(3)

3640

(0.19)

(0.21)

(0.00)

χ2 (8) = 417.14 (0.0000)

0.0610 (1.88)

0.0915** (2.15)

–

(5)

(7)

3445

(0.15)

(0.25)

(0.00)

χ2 (8) = 489.11 (0.0000)

0.0621 (1.15)

0.1331** (2.51)

3640

(0.17)

(0.21)

(0.00)

χ2 (15) = 321.27 (0.0000)

0.0812* (1.73)

0.0911** (2.29)

−0.0924** – (−2.33)

(6)

3640

(0.18)

(0.29)

(0.00)

χ2 (15) = 414.71 (0.0000)

0.0741* (1.87)

0.1059** (2.33)

–

(8)

3445

(0.19)

(0.27)

(0.00)

χ2 (15) = 325.21 (0.0000)

0.0911 (1.18)

0.1156** (2.35)

−0.0971* (−1.84)

(9)

Coefficient (z)

Note I /K is the dependent variable where I = net investment in fixed assets, K = capital stock at the beginning of the period, C F = cash flow, S = sales, Q = Tobin’s Q ratio, T I E = total interest expenses, T B = total borrowings, Q = Tobin’s Q ratio, L I Q = liquidity, L E V = leverage, S Z = firm size, T AN = tangible assets, and AG E = firm age, i = number of firms represented as 1, 2,…,n, and t = time period. (ii) ***, ** and * show the 1%, 5% and 10% level of significance respectively. (iii) z-statistics given in the parenthesis. (iv) m 1 (m 2 ) is a test for first- (second-) order serial correlation in the first-differenced residuals, asymptotically distributed as N(0,1) under the null of no serial correlation. (v) Wald test is a test of joint significance of the estimated coefficients which is asymptotically distributed as chi-square under the null of no relationship and Sargan test of over identifying restrictions, which is asymptotically distributed as chi-square under the null of instrumental validity. (vi) NOB is the number of observations. (vii) F I D A, F I D B, and F I DC considered as financial distress measurement by Altman’s Z”-Score model, financial distress ratio, and Ohlson’s O score model respectively

(0.00) (0.29)

(0.00)

(0.29)

χ2 (8) = 388.98 (0.0000)

χ2 (8) = 316.96 (0.0000)

Wald test

m 1 (p)

0.0804** (2.11)

0.0804* (1.67)

Constant

m 2 (p)

0.1347** (2.18)

0.1158** (2.49)

BGit

(2) –

(1)

–

Coefficient (z)

Euler equation with financial distress Extended model with financial distress

Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient Coefficient (z) (z) (z) (z) (z) (z) (z)

Q model specification with financial distress

FDC it

Variables

Table 6.9 (continued)

168 J. Mahakud and G. Gupta

6 Business Group Affiliation, Financial Distress and Corporate …

169

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Chapter 7

Promoter Ownership and Performance in Publicly Listed Firms in India: Does Group Affiliation Matter? Ansgar Richter and Indrani Chakraborty

Abstract Many of the largest Indian firms are characterized by promoter ownership, a hybrid form of ownership and governance in which the companies’ founders or their heirs hold controlling stakes, while inviting external minority shareholders to contribute capital, and outside managers to participate in the day-to-day administration of the companies concerned. We analyze a sample of 4056 publicly quoted firms with promoter ownership in India during 2007–2013. We find that in groupaffiliated firms, the level of promoter ownership has no effect on performance of firms, as measured by Tobin’s q and return on assets (ROA). However, in stand-alone firms, the level of promoter ownership has a U-shaped relationship with Tobin’s q and no relationship with ROA. Moreover, group-affiliated firms show lower performance than stand-alone firms. This seems to be due to the development of the capital market in post-reform India which has greatly reduced the financing constraints for both group-affiliated and stand-alone firms.

7.1 Introduction In the Indian economy, many firms are fully or partially owned by “promoters”, individuals who, often with other family members, exercise control over the companies concerned by virtue of their shareholding and management rights (Shleifer 2005; Bertrand et al. 2002; Chong and Lopez-De-Silanes 2007). Promoter ownership implies that the ownership rights in a firm are relatively concentrated in the hands of an internal party, either an individual or a family that is closely connected with the company, even if external shareholders may participate in the ownership structure (Balasubramanian and Anand 2013; Kumar and Singh 2013). A. Richter Rotterdam School of Management, Erasmus University, Rotterdam, Netherlands I. Chakraborty (B) Institute of Development Studies, Kolkata, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_7

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According to the corporate governance literature, such concentrated ownership among insiders has both benefits and costs as compared to the ownership of firms by dispersed groups of external shareholders (Claessens et al. 2002). On the one hand, promoters tend to have greater commitment to the firms in which they are invested than more neutral, external shareholders, and are thus more likely to make decisions that maximize firm value in the long run (Anderson and Reeb 2003a, b). On the other hand, there is a danger that promoter-owners become entrenched in their companies, and that they engage in tunneling behaviors through which they transfer value to their own advantage, while shifting costs and liabilities to outside minority shareholders (Morck et al. 2005). There is a rich theoretical and empirical literature on the relationship between insider ownership and firm performance (e.g., Jensen and Meckling 1976; Fama 1980; Jensen and Murphy 1990; Jensen 2000). However, this literature relates primarily to the allocation of comparatively small ownership stakes to managers in order to overcome managerial agency problems and align their interests with those of external shareholders (Morck et al. 1988; McConnell and Servaes 1990; Loderer and Martin 1997; Himmelberg et al. 1999; Short and Keasey 1999; Fahlenbach and Stulz 2009). It is thus not clear whether the evidence on the relationship between managerial ownership and firm performance produced in this literature is applicable to the inside ownership by promoters, who hold direct or indirect control over their firms. Likewise, although promoter ownership in emerging economy firms may have similarities with family ownership in firms in developed countries (Morck and Yeung 2004), such that insights from the latter can be drawn to understand the former better, there are also important differences between the two concepts. Not all promoters in emerging market firms are families; some are individuals (CMIE 2014). Furthermore, promoters maintain a high level of involvement in their firms, whereas in some family-owned firms in the developed market context, the owning families play a more passive role (Handler 1994). Little is known about the relationship between promoter ownership and performance in emerging market firms, and the empirical evidence available so far (e.g., Kumar and Singh 2013) suffers from a number of methodological limitations. Moreover, in the extant governance literature, promoter ownership is often equated with firm affiliation in pyramidal groups (Khanna and Palepu 2000a), in which the tunneling behavior sketched above is said to be particularly virulent (Bertrand et al. 2002). In contrast, there are many promoter-owned firms that operate on a stand-alone basis i.e., that are not part of a larger group of firms connected through a system of cross-shareholdings and personal relationships (Balasubramanian and Anand 2013). In these stand-alone firms, promoter shareholders tend to have more direct managerial involvement, as they can concentrate their efforts more closely on a particular company, rather than to spread them across an entire portfolio of diverse investments as is the case in group-affiliated firms (Joern et al. 2010). According to this line of argument, stand-alone firms with promoter ownership should show higher levels of performance than group-affiliated firms, as tunneling behaviors should be less prevalent in the former than in the latter.

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In this paper, we investigate the relationship between promoter ownership and performance in a large panel of group-affiliated and stand-alone firms quoted on the Indian stock market between 2007 and 2013. We also analyze whether the effects of promoter ownership hold for different dimensions of firm performance namely, capital market performance and accounting performance. Furthermore, we provide an advance over existing studies by taking into account the dynamic nature of the dependent variable (firm performance), by using a dynamic panel data (DPD) regression approach. The structure of the paper is as follows. In the next section we review the theoretical arguments as well as the empirical evidence with respect to the relationship between the insider and family ownership and firm performance, and discuss its applicability to the case of promoter ownership. Furthermore, we introduce the distinction between group-affiliated and stand-alone firms, specifically in the Indian context on which our analysis focuses. Thereafter, we describe the data used in this study and discuss the measures and methods employed. Finally, we present the results of our analysis and discuss their theoretical and managerial implications. We also point out the limitations of our study, and sketch avenues for future research.

7.2 Review and Hypotheses 7.2.1 The Role of Promoter Ownership in Indian Firms According to the seminal paper by La Porta et al. (1999), a large proportion of corporate ownership around the world is not in the hands of outside shareholders, but rather it is held by parties that are more closely connected with the firms they own, such as founders and families. One special form of ownership allocation that has received relatively little attention in both the corporate finance and the management literatures is the ownership of Indian firms by the so-called “promoters”. Kumar and Singh (2013: 91) define the term promoter loosely as “a person or a group of persons who is/are involved in the incorporation and organization of a corporation”. More formally, promoter ownership has three major characteristics. First, according to SEBI’s Disclosure and Investor Protection (DIP) Guidelines (2000) and the Indian Takeover Code (1997), promoters effectively control the firm by virtue of the shareholding and management rights. In conjunction with the rapid growth of promoter-owned firms, many promoters have invited outside shareholders to participate in the ownership structure, e.g. by floating a portion of the equity on the stock market. However, even in these situations, the promoters seek to retain a stake in the company that is sufficiently large to ensure ultimate control over it (Sarkar 2010; Sarkar and Sarkar 2000; Varma 1997).

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Second, promoters tend to retain an active involvement with the company, even if they or other members of their families occupy only some, or even no, formal management positions in it. They regularly retain position as board chairs, but their involvement goes beyond the role that many external directors play in typical “Western” economies characterized by more widely dispersed shareholder structures (Khanna and Palepu 2000b). For example, promoters often play the role of lobbyists who maintain relationships with local and national governments and policy-makers in order to advance their companies’ interests. They are involved and retain the ultimate decision-making power in key investment decisions, and develop relationships with banks and financiers. Third, many, but not all, promoter-owned firms are family businesses in the sense that other family members are involved in the management of the company, and that there is an implicit or explicit expectation that the company will continue to be (majority-) owned and controlled by future generations of the family, and managed along similar lines. The promoter-owned firms where other family members (often the children of the founder-promoter) are involved are generally organized as business groups (diverse groups of firms that are connected to one another through complex networks of relationships). In contrast, in stand-alone firms, family members usually have less of an involvement with the firm. Stand-alone firms with promoter ownership rely heavily on outside managers who are in charge of much or all of the day-to-day administration of the company concerned. Overall, promoter ownership constitutes a form of hybrid model of ownership and governance, in which concentrated ownership by a particular type of “insiders” is combined with equity participation by minority shareholders and managerial participation from outside professionals. The insider ownership in promoter-owned firms differs from the managerial insider ownership discussed in the corporate finance literature by the comparatively large stake of the promoter’s ownership stake, and the resulting absence of an effective governance mechanism that would control the dominant inside owner (namely, the promoter). In the following, we discuss the expected performance consequences of this particular form of inside ownership.

7.2.2 Performance Effects of Variations in the Level of Promoter Ownership The extant literature on inside ownership is dominated by two perspectives that imply conflicting predictions regarding the relationship between inside ownership and firm performance. First, according to the ‘alignment of interest’ hypothesis (Jensen and Meckling 1976; Demsetz 1983; Fama and Jensen 1983), the inside allocation of ownership rights overcomes (or at least reduces) agency conflicts between outside shareholders and insiders (i.e., managers and/or employees) in situations of asymmetric information, costly monitoring, and opportunistic behaviour (Holmstrom and Milgrom 1991; Cable and Fitzroy 1980). Due to the active involvement of promoters,

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promoter ownership may reduce asymmetric information, thus resulting in a reduction of aggregate monitoring costs (Conte and Svejnar 1988; Demsetz 1983; Fama and Jensen 1983). If promoter shareholdings were small and the ownership rights are widely dispersed among multiple classes of shareholders, the incentives for none of the shareholder groups (neither the promoters, nor the external shareholders) might be sufficiently large for any of them to invest in monitoring. However, promoters tend to own relatively large stakes in their companies, thus tying a substantial proportion of their wealth to the fortunes of their companies. Therefore they have material incentives to monitor their companies carefully. In this situation, external shareholders are effectively able to free-ride on the efforts of the dominant owner namely, the promoter. According to this line of argument, we would expect the intensity of monitoring (and hence, firm performance) to be positively associated with the share of ownership rights held by promoters. Second, Morck et al. (1988) argue that a substantial level of inside ownership can contribute to managerial entrenchment, which adversely affects outside shareholders and thus reduces firm value. Such entrenchment may take several forms. For example, the owner-manager (in this context, the promoter) may extract pecuniary benefits for herself or family or, she may take decisions that favours ‘cronies’, or hire incompetent relatives for key positions (Bloom and Van Reenen 2007; Perez-Gonzalez 2006). Moreover, information asymmetry between the dominant promoters and minority shareholders may increase the entrenchment effect due to a lower flow of information. Less transparency will affect performance adversely (Wang 2006). An alternative perspective to explaining the insider ownership–firm performance relationship which can be applied to the case of promoter ownership is through using the managerial discretion approach, initially developed by Stultz (1990) and Zwiebel (1996). According to this approach, managers are in control of the firm and choose their ownership stake to maximize their welfare. An extension of the earlier models was developed by Fahlenbach and Stultz (2009) in which managers acquire a stake in the firm if it adds value to managers. This approach predicts that decreases in managerial ownership do not lead to decreases in firm value but increases in managerial ownership would be associated with increases in firm value (Fahlenbach and Stultz 2009). In an attempt to reconcile the two rival arguments for alignment and entrenchment sketched above, a growing body of research has suggested the existence of non-linear relationships between insider ownership and firm performance (Morck et al. 1988; Hermalin and Weisbach 1991; Davis et al. 2005; Cui and Mak 2002; Selarka 2005). Furthermore, the empirical results appear to be sensitive to model specification, the use of alternative performance measures, and the type of firms considered. Many of these studies use market-based measure of performance only (Morck et al. 1988; Hermalin and Weisbach 1991; Davies et al. 2005; Cui and Mak 2002). A large number of studies suggest a cubic relationship between insider ownership and firm value, supporting the existence of both the alignment effect and entrenchment effect (Morck et al. 1988; Short and Keasey 1999; Faccio and Lasfer 1999; Sarkar and Sarkar 2000; Hung and Chen 2009). The cubic specification, however,

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has the limitation that inflexion points are sensitive to the inclusion of control variables. Dropping one or more control variables may affect the results. Moreover, the cubic specification may not fit the data well if the non-linear relation is not smooth (Pattanayak 2001). This problem can be resolved by using piecewise linear regression as done by Morck et al. (1988). However, the inflexion points in piecewise linear regression are critical. Morck et al. (1988) chose the inflexion points arbitrarily. This approach may make the results biased due to misspecification of the model. Other studies, however, suggest that the relationship between inside ownership and performance may not be a cubic one. The relationship between insider ownership and firm performance appears to differ between family and non-family firms (Arosa et al. 2010; Selarka 2005; Khanna and Palepu 1999). Arosa et al. (2010), using accounting measure of performance found a cubic relationship between insider ownership and performance in family firms, whereas there was no relationship between the two in non-family firms. In the specific context of India, Selarka (2005) using 1397 firms for the year 2001 and based on the performance measure of market-to-book value ratio, found a U-shaped relationship between insider ownership and firm performance. The inflexion point of this relationship differed between group-affiliated (31%) and stand-alone firms (51%). Another important study in the Indian context is Khanna and Palepu (1999) who found that insider ownership has positive and significant effects on firm value. We believe that this empirical evidence may be informative with respect to the relationship between the level of promoter ownership and firm performance, too. In line with the study by Khanna and Palepu (1999), we propose the following hypothesis: Hypothesis 1: The level of promoter ownership has a positive effect on firm performance.

7.2.3 Group-Affiliation Compared to Stand-Alone Firms with Promoter Ownership As indicated above, group-affiliated firms are distinguished from stand-alone firms in two major ways. First, group-affiliated firms consist of groups of companies that are connected through a network of legal, financial and transactional relationships. According to Gopalan et al. (2007), Indian business groups are characterized by a substantial amount of intra-group financing. Comparing group-affiliated firms with stand-alone firms, Khanna and Palepu (2000a) argue that the use of internal market mechanisms reduces transactions costs among group-affiliated firms, in the absence of well-developed and efficient factor markets. They conclude that in highly diversified and large business groups in India, group-affiliation affects firm performance positively. Second, in group-affiliated firms the role of family in firm management is higher than is the case in stand-alone firms (Holderness and Sheehan 1988; Denis and Denis

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1994).Many family members play the role of leadership and provide guidance to the firm in setting the goals (Jones et al. 2008). These family leaders have attachment to their firms. Family management in group-affiliated firms are often concerned with the non-financial aspects of the business which address the family’s emotional needs. These non-financial aspects are known as “socio-emotional wealth” (SEW) and it becomes important for the family when the family managers look for growth of their firms, specifically through diversification (Gomez-Mejia et al. 2007). SEW is defined as the ability to exercise authority, the enjoyment of personal control, “clan membership”, a sense of belonging, affection, intimacy as well as an active role in the family dynasty. Family firms will not opt for diversification because it may reduce the family’s control over the managerial aspects.. Gomez-Mejia et al. (2010) argues that as diversification requires raising of additional capital through debt or stocks, it will raise the risk of financial distress and will lead to loss of family control, and consequently, family firms will be less willing to diversify. Moreover, due to diversification, outside managers will be hired which may lead to information asymmetries and increase the conflict regarding the goals of the firms and hence reduce family SEW. Also diversification requires involvement of outside parties through their expertise, which may lead to loss of control by family and hence family firms would not like diversification (Schulz et al. 2001, 2003b). However, these arguments for family firms in developed economies are not applicable in the context of an emerging economy like India. The promoter family in an emerging economy that may diversify into multiple industries and still retain control over affiliate firms through a pyramidal ownership structure and family management (Chung, 2012; Almeida and Wolfenzon 2006; La Porta et al. 1999). The extant literature has suggested that in emerging economies, the existence of imperfect markets and institutional voids are conducive to group-affiliated firms, controlled by promoter family, to gain some benefit through diversification (Khanna and Palepu 1997; Khanna and Rivkin 2001).Khanna and Palepu (2000a) find that group-affiliated firms diversify in India and after reaching a certain threshold, diversification increases firm value. On the other hand, in case of stand-alone firms, entrenched managers have the motivation for diversification so that they become valuable to shareholders and costly to replace (Shleifer and Vishny 1989). Diversification also helps the managers to diversify their employment risk (Amihud and Lev 1999), and produce several personal gains relating compensation (Stulz 1990). However, diversification reduces shareholder wealth which leads to conflict between the manager and shareholders regarding diversification (Denis et al. 1999). The effect of diversification on firm value is ambiguous. A large number of studies show that diversification is valuedestroying (Amihud and Lev 1999; Chkir and Cosset 2001; Berger and Ofek 1995; Lang and Stulz 1994, Servaes 1995). However, a recent study by Villalonga (2004) shows that diversification results in some premium, which supports the idea that the manager pursues shareholders’ interests when diversifying. However, some studies predict a negative relationship between diversification and managerial equity ownership (Denis et al. 1997, 1999) which is based on the assumption that “the manager’s private benefits from diversification are invariant with respect to the manager’s equity

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stake”. However, Chen and Ho (2000) find support for this view in some Singapore firms, where they find that diversification leads to value loss for those firms which have low managerial ownership. As a corollary to this finding, we can say that high promoter ownership leads to increase in firm value due to the diversification strategy in both group-affiliated and stand-alone firms. But Manikandan and Ramachandran (2015) raise doubts about the value-increasing effect of diversification in stand-alone firms. They argue that, in the case of diversified stand-alone firms, each firm has no separate legal entity and each firm reports to the firm’s corporate headquarters, and on the top, there is the firm’s board of directors. These diversified stand-alone firms publish a single financial statement on the performance of all these firms as a whole (Manikandan and Ramachandran 2015). Some scholars argue that the presence of the corporate headquarters as the top-level decision-maker hampers the motivation of the managers in each of the divisions of these stand-alone firms (Manikandan and Ramachandran 2015; Campbell et al. 1995; Day and Wendler 1998) and hence profitability may not be reached at the optimum level (Manikandan and Ramachandran 2015; Prahlad and Bettis 1986; Rajan et al. 2000). Furthermore, family members in group-affiliated firms generally have long time horizon (James 1999), because families try to keep control across generations. This phenomenon would provide incentive to invest in a manner that would maximize the value of the firm, and therefore would benefit minority shareholders (James 1999; McVey and Draho 2005). Furthermore, in group-affiliated firms, family ties help to control managerial selfdealing which in turn ensure the firm’s survival (Denis and Denis 1994). Due to the long-term relationships between the family and other stakeholders, transaction costs will be low (Anderson and Reeb 2003a, b; McVey and Draho 2005). Further, these firms will get fund at a lower cost because of their reputation and hence the conflicts of interests between shareholders and bondholders will be less (Anderson et al. 2003). However, some scholars point out that the entrenchment effects will be higher in group-affiliated firms relative to stand-alone firms due to the greater family involvement (Morck et al. 2005). It has been noted that entrenchment of management in family-owned firms will result in more severe agency problems than those in nonfamily firms (Gomez-Mejia et al. 2001; McVey and Draho 2005). As the family owners have greater stake in group-affiliated firms, the management of these companies will be more concerned with the family interests instead of pursuing the goal of value maximisation of the company (DeAngelo and DeAngelo 2000). Group-affiliated firms have a number of unique governance structure characteristics in comparison to stand-alone firms. One such characteristic is dependence on pyramidal ownership by promoter family to control the affiliate firms in which the control operates through cross-holdings of the other firms (Claessens et al. 2000; La Porta et al. 1999, 2002; Young et al. 2008). The advantage of this method of operation is that, it needs very little direct ownership by the promoter family. However, pyramidal ownership structure leads to a particular kind of agency problem that arises

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due to conflicts between controlling shareholders and minority shareholders. In pyramidal ownership structure of the group-affiliated firms, minority shareholders’ interests will be expropriated by the controlling shareholders (Morck and Yeung 2004) and therefore, it will adversely affect the performance of group-affiliated firms (DeAngelo and DeAngelo 2000; Morck et al. 2000; Santana et al. 2007). Anderson and Reeb (2003a, b) argue that, whereas minority shareholders would be interested in maximization of firm value, owner-managers in group-affiliated firms may pursue other objectives. As a consequence, the interests of the minority shareholders will be adversely affected. This practice of expropriation of minority shareholders by the controlling shareholders in group-affiliated firms may lead to reduced firm profitability (DeAngelo and DeAngelo 2000; Morck et al. 2000; Santana et al. 2007). In this context, Cronqvist and Nilsson (2003) argue that high levels of family ownership in group-affiliated firms lead to investment decisions which are inefficient and finally lead to a reduction in the market value of the company which in turn will have deleterious effects on minority shareholders. In the particular context of Indian firms, the evidence provided by Bertrand et al. (2002) suggests that group affiliation may reduce firm value, as group-affiliated firms are subject to the tunnelling behaviour sketched above. However, some recent studies (Manikandan and Ramachandran 2015; Foss et al. 2006) show that the presence of outside directors in each of the affiliates in groupaffiliated firms, help to check the opportunistic behaviour of the controlling shareholders. Some scholars further argue that, due to the requirement of compulsory reporting by group-affiliated firms, tunnelling becomes difficult and consequently, the management of group-affiliated firms will pursue the goal of value maximization (Almeida and Wolfenzon 2006; Belenzon and Berkovitz 2010; Manikandan and Ramachandran 2015; Foss et al. 2006). We thus propose the following hypothesis: Hypothesis 2: Ceteris paribus, group-affiliated firms have higher performance than stand-alone firms.

7.2.4 Methodological Concerns A particular concern in both the theoretical and the empirical literature with regard to the relationship between ownership allocation and firm performance relates to the possibility that ownership allocation itself may be endogenously determined by unobservable, firm-specific factors (Demsetz 1983; Demsetz and Lehn 1985). These authors show that ownership structure of U.S. firms is determined by firm size, industry affiliation and various other firm-specific variables (Demsetz and Lehn 1985). In a later study, Himmelberg et al. (1999) use a fixed effect panel data method and instrumental variables to control for unobserved firm level heterogeneity. They found that the managerial ownership has no statistically significant effect on firm performance. Some other studies, assuming endogeneity of managerial ownership

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Table 7.1 Distribution of firms in various years with entry and exit of firms 2007

2008

2009

2010

2011

2012

2013

No. of firms in year-end

2851

2951

2990

3033

3085

3130

3170

No. of firms entering

1442

117

62

65

75

87

96

35

17

23

22

23

42

56

No. of firms exiting

and applying a simultaneous equation framework, have observed reverse causality (Cho 1998; Loderer and Martin 1997; Kole 1996). Therefore, in our own approach, we choose a method that is better able to handle such endogeneity concerns than conventional cross-sectional regression approaches are.

7.3 Data and Methods 7.3.1 Data Our sample is drawn from PROWESS, a database provided by the Centre for Monitoring Indian Economy (CMIE). This database has been widely used in reputable studies on Indian firms (e.g., Khanna and Palepu 1999; Khanna and Palepu 2000a; Marisetty and Subrahmanyam 2006). It includes all Indian firms listed on the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE) during the 20072013period. The total number of firms included in the PROWESS database is 5327. We begin our analysis from 2007 as Clause 49 of the Listing Agreements to the Indian Stock Exchange, which was enacted in order to improve reporting standards and corporate governance practices in India, came into effect on December 31, 2005. Moreover, the maximum number of IPO’s were initiated in the year 2007 (see Table 7.1). We excluded firms which operate in the financial sector (banks, insurance companies and investment trust), reducing the size of the database to 4056 firms. Furthermore, we eliminated those firms for which information on shareholding patterns and other variables were missing for at least one year of the seven-year period investigated here. Our final sample involves 3363 firms with promoter ownership and 693 firms without promoter ownership. Of the firms with promoter ownership, there are 2832 firms with only Indian promoters, 520 firms with a mixed ownership structure (i.e., both Indian and foreign promoters), and 11 firms with only foreign promoters. Of the 2832 firms with Indian promoters, there are 1230 group-affiliated firms and 1602 stand-alone firms.1 Characteristics of the sample are reported in Table 7.2. 1

It may be noted that the listed group-affiliated firms have gone for initial public offering (IPO) at some point during their life time to raise capital from the market. The total number of IPOs in India during the 1990-2004 period was 484 for group-affiliated firms, and 2147 for stand-alone firms (Marisetty and Subrahmanyam 2006).

7 Promoter Ownership and Performance in Publicly Listed Firms in India … Table 7.2 Characteristics of the sample

Variables

Sample Mean

Tobin’q

185

3.656

Std. dev 130.056

ROA

0.031

1.972

IPS

39.710

25.172

4.663

3.308

SIZE GROWTH

3.719

264.471

LEVERAGE

0.841

19.989

R&D

0.010

0.032

AGE

3.085

0.614

Note N = 2832 = Firms with Indian promoter ownership; IPS = Indian promoter’s share; Tobin’s q and SIZE are reported in million Indian Rupees. ROA, IPS, GROWTH, LEVERAGE and R&D are percentages. AGE is reported in years

7.3.2 Variables Performance: As firm performance constitutes a multidimensional phenomenon (Shen and Cannella 2002a; Richard et al., 2009), we used two types of performance measures. First, as a measure of capital market performance, we used Tobin’s q, measured by the ratio of the sum of the market value of equity and the book value of debt divided by total assets. Second, we used operating return on assets (ROA), which reflects operational firm performance and is independent of short-term accounting policy manipulation (Dowdell and Krishnan 2004; Geiger and North 2006; Geiger et al. 2005). Following Huson et al. (2004), we adjusted this measure for industry effects by calculating the difference between the value of this measure for each company and the industry median in the year concerned, using the two digit industry code according to the National Industry Classification (NIC) system provided by National Accounts Statistics (Government of India 2008). Promoter ownership (PROMOWN): This variable measures the share of equity owned by the promoters of Indian firms. Promoters are defined as all individuals and their relatives, corporate bodies/trusts/partnership or any other type of entity that either founded or acquired a controlling stake in the firm concerned, where the ownership stake exceeds that of any external shareholder. Note that the Companies Act of 2013 in India stipulates the one-share-one-vote principle, so that voting rights and financial return rights do not diverge (as they often do in other countries, thus creating control-enhancing mechanisms; see Balasubramaniam and Anand 2013). Group-affiliated firms versus stand-alone firms: In the PROWESS database, group-affiliated firms are defined as those that are classified as business houses, whereas stand-alone firms are unaffiliated to other firms. In stand-alone firms, the promoters are generally individuals, rather than families with diverse business interests. Following Khanna and Palepu (1999), we note that CMIE uses several criteria for

186

A. Richter and I. Chakraborty

classifying firms into groups. Specifically, CMIE takes into account (i) the identity of the promoter of a firm upon its incorporation; it then traces whether the original owners retained their affiliation with the firm; (ii) announcements/ statements by individual firms indicating whether they belong to business groups, as well as announcements / statements by groups regarding the firms affiliated with them. Such information is contained in annual reports, statements made at the time of public offerings, acquisition announcements, and news releases about the future plans of the groups or the firms concerned; (iii) information on a firm’s group affiliation that is evident from the membership of the firm’s board of directors (Khanna and Palepu 1999). Control variables: We have included the following control variables as prior literature suggests that they may affect firm performance. Firm size (SIZE) may provide a firm with economies of scale and enhance its marketing power (Short and Keasey 1999; Pindado et al. 2008; Selarka 2005; Arosa et al. 2010). We measured SIZE as the natural logarithm of a firm’s revenues (Cui and Mak 2002; Himmelberg et al. 1999; Khanna and Palepu 2000a). We included firm growth (GROWTH), measured as the percentage change in sales in a particular year as compared to the previous year, in order to control for the effects of a firm’s growth on its performance (Short and Keasey 1999; Hermalin and Weisbach 1999; Cui and Mak 2002). Next, we included financial leverage (LEV ), as high levels of debt in a firm’s capital structure may signal that a firm has bonded itself to achieving the levels of cash flow required to meet its debt obligations (Grossman and Hart 1982; Jensen 1986). Financial leverage is measured as the ratio of total borrowing to assets (Davies et al. 2005, Short and Keasey 1999; Pindado et al. 2008; Davies et al. 2005; Cui and Mak 2002).As a firm’s research and development (R&D) intensity may affect performance, we included the ratio of its research and development expenditures to total assets, following prior literature in the field (Morck et al. 1988; McConnell and Servaes 1990; Short and Keasey 1999). Finally, the age of a firm (AGE), measured by the natural logarithm of the number of years since its incorporation, was included in our analyses (Pindado et al. 2008; Selarka 2005; Arosa et al. 2010).

7.3.3 Analytical Approach In this study we apply two different estimation methods, viz. (a) propensity score matching and (b) dynamic panel data method. To answer the question whether promoter ownership matters for firm performance, we have applied the propensity score matching technique. Then for estimating the effects of promoter ownership on performance we have applied the dynamic panel data method. In particular, we apply the dynamic panel data method to find out whether group-affiliated firms perform better than stand-alone firms. We briefly discuss both methods here. In propensity score matching method, for each firm i in the sample, let POi be the indicator of promoter ownership that equals one when the firm is owned by a promoter and zero otherwise. We denote Yit as the performance of firm i in year t

7 Promoter Ownership and Performance in Publicly Listed Firms in India …

187

when it was owned by a promoter, and Yi0 as the performance of a firm not owned by a promoter and observe POi and hence Yi = POi .Yit + (1-POi ). Yi0 . Let E[Yit |POi = 1] and E[ Yio | POi = 0] denote average performances of the promoter-owned and non-promoter-owned firms, respectively. The effect we are interested in is that of promoter ownership on firm performance of the promoter-owned firms, or the difference between the firm performance of the promoter-owned firms and the firm’s performance that would have experienced by the same group of firms if they had not been owned by promoters: τ |Poi =1 = E[Yi1 | POi + 1] − E[ Yi0 | POi = 1]

(7.1)

This denotes the expected treatment effect on the treated. Since we do not have the counterfactual evidence of what would have happened if a firm had not owned by a promoter,E[Yio | POi = 1] is unobservable. However, it can be estimated by E [Yio |POi = 0] and the effect is given by the difference in the average firm performance between the promoter-owned and non-promoter-owned performances: τ e = E[Yit | POi = 1] − E[Yi0 | POi = 0]

(7.2)

In fact, we have observations on the firms which were not owned by promoters, but if the promoter-owned and non-promoter-owned firms systematically differ in their firm characteristics, (7.2) will be a biased estimator of (7.1) (Hirano et al. 2002). Rubin (1977), Rosenbaum and Rubin (1984) showed that a propensity score analysis can be used to create groups of treated and untreated units that have similar characteristics, and then comparisons can be made within each group. In each group, there are firms that are owned by promoters and those not owned by promoters. Hence the promoter ownership can be considered to be random inside a group of firms (Gantumur and Stephan 2007). The propensity score of promoter ownership is defined as the conditional probability of being owned by the promoter given a set of observed covariates Xi : PS(POi ) = Pr (POi = 1|Xi ) = E [POi |Xi ]

(7.3)

The treatment effect of promoter ownership is then estimated as the expectation of the conditional effects over the distribution of the propensity score in the promoterowned firms:   τ Poi =1 = Eps(Poi) {E[Yi1 ps(POi ), POi = 1] − E[ Yi0 |ps(POi ), POi = 0] |POi = 1} (7.4) In order to reduce endogeneity concerns, we use dynamic panel data (DPD) models (Wintoki et al. 2009). DPD models are particularly useful when the dependent variable depends on its own past realizations (Bond 2002). Our base model is as follows:

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A. Richter and I. Chakraborty

PERFit = PERFit−1 + βPROMOWNit + δXit + αi + εit

(7.5)

where firm i = 1, . . . N and year t = 1, . . . T In this model Xit are the control variables, αi are the firm fixed effects, and the error term εit has zero mean constant variance and is uncorrelated across both time and firms. For estimation purposes, we have to remove the firm fixed effects αit from Eq. (7.5) by first differencing. Thus we obtain: PERFit − PERFit - 1 = γ (PERFit - 1 − PERFit - 2 ) + β(PROMOWNit − PROMOWNit - 1 ) + δ(Xit − Xit - 1 ) + (εit − εit - 1 )

(7.6)

Alternatively, PERFit = γPERFit−1 + βPROMOWNit + δXit + εit

(7.7)

In Eq. (7.7), the variable PERFit−1 is correlated with PERFit due to the dynamic nature of the equation. To solve this problem Anderson and Hsiao (1982) proposed to use PERFit−2 or PERFit−2 as instruments for PERFit . In fact, lagged levels of the endogenous variable PERFit , , three or more time periods before, can be used as instruments (Holtz-Eakin et al. 1988). Arellano and Bond (1991) proposed the method of Generalized Method of Moments (GMM) which uses all possible instruments. Using this method estimates were obtained based on the moment conditions generated by lagged levels of the dependent variable (PERFit−2 , PERFit−3 , …) with PERFit . These are called difference GMM estimators. Furthermore, Arellano-Bover/ Blundell-Bond developed another estimator which is based on the Arellano-Bond with an additional assumption that first differences of instrumental variables are uncorrelated with the fixed effects. This considers the introduction of additional instruments and improves efficiency (Roodman 2009). It develops a system of two equations, namely, the original equation and the transformed one, and is known as system GMM. In this study we use a system GMM method.

7.4 Results 7.4.1 Descriptive Statistics We present the summary statistics regarding the proportion of promoter ownership over 2007–2013 in Table 7.3. The evidence suggests that promoters hold approximately 50 percent of the ownership rights in the firms contained in the sample, and that this proportion increased slightly over time. The minimum percentage of equity holding by promoters fell from 8.73% in 2007 to 5.12 percent in 2013, whereas the maximum percentage of their equity holding (98.19%) remained unchanged.

7 Promoter Ownership and Performance in Publicly Listed Firms in India …

189

Table 7.3 Pattern of promoter ownership over the years in sample firms Promoter ownership (%)

2007

2008

2009

2010

2011

2012

2013

Mean

49.88

50.13

51.19

51.24

51.38

51.90

52.22

Std. dev

15.36

15.17

15.06

14.95

15.28

15.44

15.40

Minimum

8.73

8.85

5.30

5.30

5.30

5.30

5.12

Maximum

98.19

98.19

98.19

98.19

98.19

98.19

98.19

N = 19,824

Table 7.4 Summary statistics Variables

Group1: Group-affiliated firms

Group2: Stand-alone firms

Mean

Mean

Tobin’s q

1.920

ROA

0.025

IPS

49.159

Std. dev Min 17.863 0

Max 17.5

1.556 0.045 77.812 18.659 0

100

Std. dev

4.473 57.38 0.038

Min

Max

0

29.14

2.098 0.063 252

44.453 21.459 0

100

G1-G2

−3.203* −0.013 4.706*

SIZE

6.00

GROWTH

6.585 428.857 −1

42,965

2.331 77.423 −1

7282.778 4.254*

LEVERAGE

0.810

420

0.819 22.284 0

2565

3.436 2.302 15.126 7.928 0

3.946

2.986 2.302 12.814

2.054 −0.009*

R&D

0.009

0.032 0

0.963

0.011

0.032 0

0.657

−0.002

AGE

3.213

0.732 0

4.634

2.985

0.555 0

4.625

0.228

Note G1-G2: Difference between the means of variables in group-affiliated firms and stand-alone firms. N = 8610 for group-affiliated firms. N = 11,214 for stand-alone firms. * p < 0.05. Tobin’s q and SIZE are reported in million Indian Rupees. ROA, IPS, GROWTH, LEVERAGE and R&D are in percentages. AGE is reported in years

Overall, we do not find an indication that, over the seven year period investigated here, promoters tend to decrease their ownership stakes, which one would expect given the growth of these firms. Table 7.4 reports the descriptive statistics for the variables in this study, distinguishing between group-affiliated firms and stand-alone firms. Overall, groupaffiliated firms are significantly larger and older than stand-alone firms, and their R&D expenditures (relative to their size) are higher. Furthermore, the group-affiliated firms in the sample show lower performance than stand-alone firms, both in terms of capital market performance (Tobin’s q), and in terms of industry-adjusted ROA, and a Z-test shows that these differences are statistically significant. These results cast doubt on Hypothesis 2, according to which group-affiliated firms are expected to outperform stand-alone firms. Surprisingly, the group-affiliated firms have higher levels of promoter ownership than stand-alone firms. Table 7.5 presents the correlations between the variables in this study. Promoter ownership is negatively correlated with Tobin’s q and positively with ROA. It is positively correlated with, age and size and negatively correlated with growth, leverage

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A. Richter and I. Chakraborty

Table 7.5 Correlation matrix Tobin’s q Tobin’s q

ROA

PS

SIZE

GROWTH

LEV1

R&D

AGE

1.00

ROA

−0.0006

1.00

PS

−0.021

0.012

1.00

SIZE

−0.014

0.003

0.155

GROWTH

−0.0003

0.0001

LEV1

−0.0007

R&D AGE

1.00

0.002

0.014

−0.010

0.006

−0.035

−0.0008

1.00 1.00

0.006

0.002

−0.053

−0.101

−0.006

−0.007

−0.005

0.005

0.084

0.131

-0.017

0.011

1.00 −0.031

1.00

N = 28,392. Note None of the correlations is statistically significant

Table 7.6 Results for propensity score matching

Tobin’s q

ROA

Average Treatment Effect

Coefficient

Coefficient

PO (1vs 0)

−8.274 (5.614)

0.010 (0. 016)

N = 283

and research and development expenditures. None of the correlations among the independent variables raises multicollinearity concerns.

7.4.2 Propensity Score Matching (PSM) Results For PSM analysis, we have taken all 4056 firms, of which 3363 firms are ‘treated’ with promoter ownership and 693 firms are ‘untreated’. Results of PSM reported in Table 7.6 show that, on average, Tobin’s q is less by 8.27 million Indian rupees in promoter owned firms than that in comparable firms that were not promoterowned. This difference in performance is, however, statistically insignificant, and therefore Hypothesis 1 is rejected, which implies, as a means for improving firm performance, promoter ownership appears to be an ineffective means. However, for ROA, there is no difference in performances between promoter-owned firms and non-promoter-owned firms.

7.4.3 Regression Results We tested the hypotheses first in the context of a system GMM approach, using the entire sample of firms. Table 7.7 presents the results of these analyses for both

7 Promoter Ownership and Performance in Publicly Listed Firms in India …

191

performance measures as dependent variables. For each dependent variable (Tobin’s q and ROA) we estimated four models. All models have good model fit, as indicated by the Wald Chi-square statistic. The baseline models 1.1 and 2.1 include the control variables, namely firm size, firm growth, leverage, research and development expenditures and firm age and the dummy for promoter ownership (DPROMOWN) which takes the value 1 if the firm is owned by a promoter and zero otherwise. In the baseline model 1.1 with Tobin’s q as dependent variable, the coefficient for firm age is only statistically significant and the variable DPROMOWN is statically insignificant. We then tested Hypothesis 1 by including the linear, the quadratic and the cubic terms of the variable promoter’s share (PS) in models 1.2, 1.3 and 1.4 respectively. We find the linear term of the promoter’s share variable in model 1.2 to be positive but insignificant. In model 1.3, where we include the quadratic variable of PS, the Wald Chi-square value of the model decreases slightly. Overall, the results suggest that promoter ownership has no positive effect on Tobin’s q, in contrast to Hypothesis 1. Moreover, we do not find support for the hypothesized effects of promoter ownership when ROA is used as the dependent variable (see models 2.1–2.4 in Table 7.7). Then we split the entire sample into two different groups: (a) firms with ownership of only Indian promoters and (b) firms with ownership of mixed groups and foreign promoters and run system GMM separately for these two groups. The regression results for (a) and (b) are reported in Table 7.8 and Table 7.9, respectively. The baseline models 1.1 and 2.1 in Tables 7.8 and 7.9 include the control variables as earlier. In Table 7.8, in the baseline model 1.1 with Tobin’s q as the dependent variable, the coefficient for age is positively significant. We then tested for Hypothesis 1 by including the linear, the quadratic and the cubic terms of the variable Indian promoter’s share (IPS) in models 1.2, 1.3, and 1.4 respectively. We find that the linear, the quadratic and the cubic terms of the variable IPS are not significant in models 1.2, 1.3 and 1.4. The results suggest that promoter ownership has no effect on Tobin’s q in Indian promoter–owned firms, contrary to Hypothesis 1. With respect to ROA also we have obtained similar results (see models 2.1, 2.2 and 2.4 in Table 7.8). System GMM results for the firms owned by mixed group and foreign promoters are reported in Table 7.9. In model 1.1, the coefficients for size and age are statistically significant. Then we find the linear term of the promoter’s share (PS) variable in model 1.2 to be positive and weakly significant at 10% level. Overall, the results suggest that promoter ownership has no significant effect on Tobin’s q in contrast with Hypothesis 1. Moreover, we do not find support for the hypothesized effects of promoter ownership when ROA is used as the dependent variable (see models 2.1–2.4 in Table 7.9). In order to provide a more differentiated understanding of promoter ownership as an antecedent of firm performance, we implement our analysis in a system GMM model, splitting the sample between group-affiliated and stand-alone firms for Indian promoter-owned firms. Results of the system GMM regressions for group-affiliated firms are presented in Table 7.10. All models have good model fit, as indicated by the Wald chi-square statistic. In the baseline model 1.1 with Tobin’s q as dependent variable, the coefficients for all control variables are statistically insignificant, except

93.774 (22.759)***

0.683 (0.005)***

Tobin’s qit-1

0.00007 (0.002)

−0.004 (0.033)

−0.414 (0.791)ϯ

0.00007 (0.002)

−0.004 (0.033)

GROWTH

LEVERAGE

−0.429 (0.792)

0.084 (0.109)

0.683 (0.005)***

94.647 (22.791)***

SIZE

PS3

PS2

PS

ROAit-1

1.4

−0.004 (0.033)

0.00008 (0.002)

−0.434 (0.792)

0.013 (0.019)

−0.001 (0.004)

−0.004 (0.033)

0.00008 (0.002)

−0.434 (0.792)

-0.0001 (0.0001)

−0.350 (0.787)***

0.683 (0.005)***

95.551 (22.949)***

−0.189 (0.368)

0.683 (0.005)***

94.478 (22.799)***

0.015 (0.0005)***

−8.94e-06 (0.00003)

−8.91e-06 (0.00003) 0.015 (0.0004)***

0.056 (0.011)***

0.001 (0.001)

0.014 (0.004)***

0.339 (0.336)

2.2

0.057 (0.011)***

0.014 (0.004)***

0.330 (0.336)

2.1

1.3

2. ROA

1.2

1. Tobin’s q

1.1

Constant

Variables

Table 7.7 Results for system GMM regressions using Tobin’s q and ROA for all firms

0.015 (0.0005)***

−8.86e-06 (0.00003)

0.056 (0.011)***

−0.00002 (0.00005)

0.003 (0.005)

0.014 (0.004)***

0.337 (0.336)

2.3

(continued)

0.015 (0.0005)***

−8.89e-06 (0.00003)

0.056 (0.011)***

4.58e-07 (2.06e-06)

−0.00008 (0.0002))

0.005 (0.011)

0.014 (0.004)***

0.334 (0.336)

2.4

192 A. Richter and I. Chakraborty

−9.805 (6.935)

−5.897 (4.744)

17,400.03***

DPROMOWN

Wald Chi-square value

N = 28,392.ϯ p < 0.1; * P < 0.05; ** P < 0.01; *** P < 0.00

27,399.89***

−27.431 (7.520)***

−27.116 (7.507)***

AGE

27,399.20***

−11.561 (9.100)

−27.389 (7.52)***

17,399.03***

−7.253 (10.669)

−27.751 (7.530)***

1145.32***

−0.090 (0.070)

09.177 (0.110)ϯ

3.320 (0.616)***

−100.155 (41.463)**

−99.808 (41.460)**

R&D

−100.666 (61.469)**

2.1

−100.279 (41.455)**

2. ROA 1.4

1.1

1.3

1.2

1. Tobin’s q

Variables

Table 7.7 (continued)

1146.63***

−0.141 (0.102)

−0.180 (0.110)ϯ

3.315 (0.616)***

2.2

1146.78***

−0.177 (0.134)

−0.180 (0.110)ϯ

3,312 (0.616)***

2.3

1146.87***

−0.195 (0.158)

−0.179 (0.111)ϯ

3.312 (0.616)_***

2.4

7 Promoter Ownership and Performance in Publicly Listed Firms in India … 193

658.410 (55.583)***

0.633 ()0.006)***

Tobin’s qit-1

0.075 (0.851)

−5.43e-06 (0.002)

−0.003 (0.034)

0.051 (0.849)

−1.63e-06 (0.002)

−0.003 (0.034)

GROWTH

LEVERAGE

−0.016 (0.040)***

0.633 (0.006)***

657.756 (55.645)***

SIZE

IPS3

IPS2

IPS

ROAit-1

1.4

−0.003 (0.034)

−0.00001 (0.002)

0.093 (0.852)

0.001 (0.003)

−0.144 (0.250)

0.633 (0.006)***

657.943 (55.648)***

−0.003 (0.034)

−2.47e-07 (0.002)

0.100 (0.852)

-0.0001 (0.0001)

0.020 (0.016)

−0.698 (0.529)

0.633 (0.006)***

658.861 (55.654)***

0.015 (0.0005)***

−8.55e-06 (0.00003)

0.058 (0.012)***

0.012 (0.004)**

1.157 (0.517)ϯ

2. ROA 1.3

2.1

1.2

1. Tobin’s q

1.1

Constant

Variables

Table 7.8 Results for system GMM regressions using Tobin’s q and ROA for Indian promoter-owned firms

0.015 (0.0005)***

−8.55e-06 (0.00003)***

0.058 (0.012)***

−0.0006 (0.001)

0.012 (0.004)**

1.154 (0.507)*

2.2

0.016 (0.0005)***

−8.71e-06 (0.00003)

0.059 (0.012)***

0.00004 (0.00004)

−0.003 (0.003)

0.012 (0.004)**

1.164 (0.518)**

2.3

(continued)

0.015 (0.0005)***

−8.64e-06 (0.00003)

0.059 (0.012)***

-7.40e-07 (1.87e-06)

0.0001 (0.0002)

−0.006 (0.007)

0.012 (0.004)**

1.172 (0.518)**

2.4

194 A. Richter and I. Chakraborty

−1856.008 (169.4721)***

−1856.646 (169.384)***

15,960.92***

DGROUP

Wald Chi-square value

15,959.15***

−1854.484 (169.499)***

−31.928 (8.122)***

N = 21,802.ϯ P < 0.1; * P < 0.05; ** P < 0.01; *** P < 0.001

15,959.85***

−32.047 (8.119)***

−32.336 (8.016)***

AGE

15,959.94***

−1852.079 (169.515)***

−32.105 (8.124)***

1097.90***

−2.565 (1.106)*

−0.220 (0.118)ϯ

3.203 (0.643)***

−74.006 (43.833)ϯ

−73.145 (43.773)ϯ

R&D

−76.920 (43.897)ϯ

2.1

−74.926 (43.861)ϯ

2. ROA 1.4

1.1

1.3

1.2

1. Tobin’s q

Variables

Table 7.8 (continued)

1097.95***

−2.561 (1.106)**

−0.212 (0.119)ϯ

3.192 (0.643)***

2.2

1098.63***

−2.553 (1.106)**

−0.209 (0.119)ϯ

3.181 (0.644)***

2.3

1098.77***

−2.567 (1.106)**

3.172 (0.644)ϯ

3.272 (0.645)***

2.4

7 Promoter Ownership and Performance in Publicly Listed Firms in India … 195

0.015 (0.205)

−12.579 (39.207)

13.759 (3.873)***

63.16***

0.015 (0.205)

−12.549 (39.167)

13.887 (3.734)***

63.19***

LEVERAGE

R&D

AGE

Wald Chi-square value

N = 2546.ϯ P < 0.1; * P < 0.05; ** P < 0.01; *** P < 0.001

0.045 (0.066)

0.046 (0.066)

GROWTH

−1.032 (0.523)**

−1.028 (0.522)**

SIZE

PS3

PS2

PS

0.004 (0.044)

−0.114 (0.016)***

−0.113 (0.016)***

Tobin’s qit-1

ROAit-1

1.2

−34.622 (11.764)**

1.1

−34.828 (11.712)**

1. Tobin’s q

Constant

Variables 1.3

63.38***

13.900 (3.921)***

−12.242 (39.250)

0.015 (0.205)

0.046 (0.067)

−1.029 (0.524)**

0.0003 (0.001)

−0.023 (0.125)

−0.113 (0.016)***

−34.722 (11.776)**

1.4

65.21***

14.188 (3.930)***

−10.696 (39.307)

0.017 (0.205)

0.049 (0.067)

−1.024 (0.524)**

−0.0001 (0.00007)

0.014 (0.009)

−0.468 )0.328)

−0.112 (0.016)***

−34.198 (11.794)**

2.2

154.94***

0.008 (0.192)

2.3

155.97***

−0.029 (0.199)

−0.008 (0.199)

−0.137 (0.011)***

0.0001 (0.004)

−0.013 (0.028)

156.03***

−0.025 (0.199)

3.120 (2.269)

−0.137 (0.011)***

0.0002 (0.003)

−0.013 (0.028)

−1.26e-06 (6.21e-06)

0.00008 (0.0005)

−0.00008 (0.00008)

−0.034 (0.012)*** 0.002 (0.019)

3.111 (2.268)

155.02***

2.4 0.130 (0.621)

0.007 (0.007)

−0.033 (0.012)**

0.125 (0.621)

3.193 (2.260)

−0.136 (0.011)***

−0.136 (0.011)*** 3.217 (2.265)

0.0003 (0.003)

−0.013 (0.028)

0.0008 (0.002)

−0.033 )0.012)**

0.140 (0.621)

0.0004 (0.004)

−0.012 (0.028)

−0.032 (0.011)**

0.122 (0.620)

2.1

1. ROA

Table 7.9 Results for system GMM regressions using Tobin’s q and ROA for mixed group and foreign promoter owned firms

196 A. Richter and I. Chakraborty

7 Promoter Ownership and Performance in Publicly Listed Firms in India …

197

age. In the baseline model 2.1 where ROA is the dependent variable, we get similar results. In models 1.2 and 2.2, we added the linear term of promoter share (IPS), our central independent variable of interest. In model 1.2, the coefficient for this variable is positive but statistically insignificant, and its inclusion increases the model fit considerably. We then added both the quadratic and the cubic term of IPS in models 1.3 and 1.4. In both cases, the coefficients on these variables are statistically insignificant. However, model fit increases in 1.3 compared to 1.2 and but then decreases further in 1.4. Thus, the “best” model is 1.3 which shows no relationship between promoter ownership and Tobin’s q. In system dynamic panel models, Wald statistics should be used to decide on the selection of the optimal model (Candelon et al. 2012). Model 1.3 thus constitutes the best representation of the determinants of Tobin’s q in group-affiliated firms. Therefore, we conclude that promoter ownership has no effects on capital market performance. By contrast, when ROA is used as the performance variable, model 2.4 has higher Wald chi-square statistics than any of the models 2.1, 2.2 and 2.3 that include no, linear, or quadratic terms of the IPS variable. However, none of the variables on promoter ownership is significant in 2.4. Therefore, promoter ownership has no relationship with ROA in group-affiliated firms. We then proceeded to analyse the performance effects of promoter ownership in stand-alone firms in firms with Indian promoters. To this end, we ran the system GMM regressions reported in Table 7.11. In the controls-only model (1.1) with Tobin’s q as the dependent variable, R&D has negative effects. We then included the linear, quadric and cubic values of the promoter share variable (IPS) in models 1.2, 1.3 and 1.4 respectively. The model with the highest Wald chi square statistic is model 1.3 with significant quadratic terms for IPS. These findings show that promoter ownership has an U-shaped relationship withTobin’s q in stand-alone firms. However, we do not find support for Hypothesis 1 when ROA is used as the dependent variable. In model 2.1, where ROA is the dependent variable, two of the controls are statistically significant, namely LEVERAGE and R&D. When promoter share (IPS) is included in model 2.2, the coefficient on IPS is negative and insignificant, and, the inclusion of this variable leads to a reduction in model fit. Furthermore, models 2.3 and 2.4, which include the quadratic and the cubic terms of IPS, have lower Wald chi square statistics than model 2.1. Therefore, promoter ownership does not appear to have a significant effect on ROA in stand-alone firms. Overall, the results presented in Tables 7.10 and 7.11 suggest that promoter ownership does not enhance performance in group-affiliated firms with Indian promoters, in contrast with Hypothesis 1. In stand-alone firms, there is a U-shaped relationship between promoter ownership and performance measured by Tobin’s q. However, there is no relationship between promoter ownership and performance for ROA. For the test of Hypothesis 2 regarding performance differentials between standalone and group-affiliated firms in Indian promoter-owned firms, we return to our system GMM regression (Table 7.8), which includes a dummy variable for group affiliation (DGROUP). When Tobin’s q is used as dependent variable, we find this variable to be negative and statistically significant in all the models. Thus, after

5.944 (12.280)

−13.947 (1.892)***

1632.02***

6.12e-06 (0.0004)

0.005 (0.039)

5.503 (12.269)

−13.438 (1.856)***

1631.12***

GROWTH

LEVERAGE

R&D

AGE

Wald Chi-square value

N = 8610.ϯ P < 0.1; * P < 0.05; ** P < 0.01; *** P < 0.001

0.005 (0.039)

6.47e-06 (0.0004)

−0.244 (0.226)

−0.282 (0.229)

0.033 (0.020)ϯ

SIZE

IPS3

IPS2

IPS

ROAit-1

0.382 (0.009)***

Tobin’s qit-1

0.282 (0.009)***

46.567 (5.910)***

46.179 (5.895)***

1632.91***

−14.105 91.898)***

6.194 (12.285)

0.005 (0.039)

0.00001 (0.0004)

−0.294 (0.229)

−0.0009 (0.004)

−0.001 (0.0009)

1632.50***

−14.103 (1.898)***

6.220 (12.299)

0.005 (0.039)

0.00001 (0.0004)

−0.294 (0.229)

−8.93e-07 (0.00003)

0.106 (0.147)

0.382 (0.009)***

46.345 (5.916)***

1.4

0.109 (0.070)

0.382 (0.009)***

46.350 (5.911)***

1.3

−0.011 (0.003)***

−0.011 (0.003)***

41.91***

−0.232 (0.165)

41.92***

−0.225 (0.169)

3.682 (1.080)***

−0.00001 (0.00003)

−0.00001 (0.00003)

3.685 (1.080)***

0.095 (0.020)***

−0.001 (0.006)

−0.0004 (0.002)

41.91***

−0.222 (0.169)

3.683 (1.080)***

−0.011 (0.003)***

−0.00001 (0.00003)

0.095 (0.020)***

0.00002 (0.00007)

−0.005 (0.007)

0.167 (0.529)

2.3

−0.005 (0.007)

0.162 (0.529)

2.2

0.095 (0.019)

−0.005 (0.007)

0.167 (0.527)

2.1

1.2

1.1

2. ROA

1. Tobin’s q

Constant

Variables

Table 7.10 Results for System GMM Regressions Using Tobin’s q and ROA for Group-affiliated Firms Owned by Indian Promoters

43.63***

−0.016 (0.012)

3.636 (1.081)***

−0.011 (0.003)***

−0.00001 (0.00003)

0.096 (0.020)***

−3.81e-06 (2.95e-06)

0.0005 (0.0004)

−0.016 (0.012)

−0.005 (0.007)

0.205 (0.530)

2.4

198 A. Richter and I. Chakraborty

0.633 (0.006)***

Tobin’s qit-1

−0.006 (0.038)

−152.888 (54.320)***

−39.812 (9.296)***

12,322.97***

0.002 (0.014)

−0.006 (0.038)

−148.709 (54.248)***

−41.470 (9.212)***

12,322.74***

GROWTH

LEVERAGE

R&D

AGE

Wald Chi-square value

N = 11,214.ϯ p < 0.1; * p < 0.05; ** p < 0.01; *** p < 0.001

0.002 (0.014)

−1.497 (1.026)

−1.416 (1.027)

−0.117 (0.092)

0.633 (0.005)***

133.545 (27.493)***

SIZE

IPS3

IPS2

IPS

ROAit-1

134.391 (27.498)***

12,323.98***

−39.282 (9.302)***

−156.055 (54.350)**

−0.005 (0.038)

0.002 (0.014)

−1.333 (1.029)

0.006 (0.004)*

−0.592 (0.278)**

0.633 (0.005)***

135.253 (27.517)***

12,325.66***

−30.674 (9.305)***

−159.439 (54.382)**

−0.006 (0.038)

0.002 (0.014)

−1.334 (1.029)

−0.0002 (0.0001)*

0.039 (0.018)**

−1.545 (0.598)*

0.632 (0.005)***

138.749 (27.583)***

559.29***

−0.250 (0.177)

2.222 (1.021)**

0.016 (0.0007)***

0.00008 (0.0002)

0.006 (0.019)

0.012 (0.004***

0.725 (0.529)

2.1

1.4

2. ROA 1.3

1.1

1.2

1. Tobin’s q

Constant

Variables

559.27***

−0.247 (0.178)

2.217 (1.023)**

0.016 (0.0007)***

0.00008 90.0002)

0.007 (0.019)

−0.0003 (0.002)

0.012 (0.004)***

0.728 (0.529)

2.2

Table 7.11 Results for system GMM regressions using Tobin’s q and ROA for stand-alone firms owned by Indian promoters

559.24***

−0.246 (0.178)

2.212 (1.024)**

0.016 (0.0007)***

0.00008 (0.0002)

0.007 90.019)

5.96e-06 (0.00007)

−0.0008 (0.005)

0.012 90.005)***

0.730 (0.529)

2.3

559.28***

−0.245 (0.178)

2.222 (1.024)**

0.016 90.0007)***

0.00008 (0.0002)

0.007 (0.019)

7.39e-07 (2.77e-06)

−0.00008 (0.0003)

0.002 (0.011)

0.012 (0.004)***

0.720 (0.530)

2.4

7 Promoter Ownership and Performance in Publicly Listed Firms in India … 199

200

A. Richter and I. Chakraborty

controlling for other factors, group-affiliated firms show the lower level of capitalmarkets performance than stand-alone firms, in contrast to Hypothesis 2. When ROA is used as a dependent variable, however, the dummy variable denoting group affiliation is again negative and statistically significant in all the models. These results therefore contradict Hypothesis 2. After controlling for other factors, such as differences in scale, leverage and others, group-affiliated firms appear to have lower accounting returns than stand-alone firms.

7.5 Discussion and Conclusion The objective of this study was to explore the relationship between promoter ownership and firm performance using a sample of Indian publicly listed firms for the period from 2007 to 2013, differentiating between group-affiliated and stand-alone firms. We described promoter ownership as a hybrid form of ownership and governance that combines majority ownership and control by insiders (namely, the promoters) with an active involvement and participation by outside shareholders and managers. We have tested two hypotheses in this study. Hypothesis 1 states that promoter ownership has a positive effect on firm performance. However, we find no support for this hypothesis. Moreover, the results (Tables 7.10 and 7.11) suggest that promoter ownership has no effect on capital market performance in group-affiliated firms. However, in stand-alone firms, promoter ownership has a U-shaped relationship with Tobin’s q. Furthermore, Hypothesis 1 is not supported when using ROA as the dependent variable in both group-affiliated and stand-alone firms. The argument for such a relationship follows from our review of the theoretical literature (Morck et al. 1988; Bloom and Van Reenen 2007; Perez-Gonzalez 2006; Wang 2006). According to this literature, large promoter ownership may lead to managerial entrenchment, which adversely affects firm performance. According to Hypothesis 2 we expected group-affiliated firms to have higher performance than stand-alone firms. In contrast to this hypothesis, the results show that group-affiliated firms have lower level of capital markets performance than stand-alone firms. The analysis using ROA as the dependent variable also provides similar results. The development of capital markets in post-reform India has greatly reduced financing constraints for both group-affiliated and stand-alone firms. Therefore, the advantage of stronger internal capital market of the group-affiliated firms is no longer playing any role to lead to higher performance by group-affiliated firms than stand-alone firms. Another potential explanatory route might relate to the degree of diversification of group-affiliated firms in emerging economies (Bamiatzi et al. 2014; Carney et al. 2008). The presence of family management in group-affiliated firms is harmful for other kinds of managerial capabilities required for diversification (Gomez-Mejia et. al., 2007, 2010). In case of developed economies, it has been observed that the agency problem does not arise if independent directors are present on the board or if the family members accumulate outside information for

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their businesses and as a result performance will not hamper (Anderson and Reeb 2003a, 2003b; Cruz et. al. 2010). However, in emerging economies, getting outside information by the family owners is much difficult due to imperfect institutions and rules for corporate governance do not require that the independent directors will be in majority on the board (Morck et al. 2005; Young et al. 2008). Hence, family management in group-affiliated firms has the disadvantage in getting the flow of new ideas which generate inadequate managerial capabilities for decision-making (Morck and Yeung 2003; Young et al. 2008). Moreover, due to the entrenchment of managers in group-affiliated firms, conflicts of interest arise between generations and it adversely affects the ability to acquire improved managerial capabilities which is needed for diversification (Morck et al. 2005; Morck and Yeung 2003).

7.5.1 Limitations and Directions for Future Research Our study has some limitations that should be addressed in future research. First, more work of both a theoretical and an empirical nature is needed to understand the phenomenon of promoter ownership more fully. Little is known to date about the nature of this specific form of ownership, and its consequences for the governance of the firms concerned. For example, while this paper focuses on a few select classes of stakeholders only (inside and outside shareholders, etc.), hardly any evidence is available with respect to stakeholder groups such as employees, and customers. Another area of interest relates to the public welfare consequences of promoter ownership. Further research on these issues is urgently needed. Second, our sample focuses on relatively young group-affiliated listed firms which are controlled by the founding family. In such group-affiliated firms, managers are likely to be from the family members. However, the decision to select managers is crucial in descendant-controlled, group-affiliated firms. Prior literature has shown that if a manager in a descendant-controlled firm is from outside the family, firm value tends to increase, whereas management by family managers is associated with a decline in firm value (Pindado et al. 2008; Barontini and Caprio 2006). The behaviour of managers of descendant-controlled group-affiliated firms with promoter ownership might be different from the ones we have analysed here. Future research should explore the performance effects of promoter ownership in such firms. Finally, the regression models used in this paper help resolve some, but not all endogeneity issues. Specifically, DPD regression addresses problem of simultaneity i.e., the possibility that the variables included in the model are endogenous to one another (Wintoki et al. 2009). However, it does not consider other types of endogeneity concerns, e.g., those arising from omitted variable bias, sample selection bias or measurement error (Antonakis et al. 2010). We believe that future research should consider these issues.

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Chapter 8

Differences in the Performance of Group-Affiliated and Stand-Alone Firms Jhuma Mukhopadhyay

Abstract In this study, we try to find out whether group-affiliated firms perform better than the stand-alone firms in the post-reform period. Our study is based on the 14,274 numbers of BSE-listed manufacturing firms. Using dynamic panel data regression technique, we find that group-affiliated firms outperform the stand-alone firms. In order to find the factors responsible for better performance of affiliated firms, we again apply dynamic panel data regression technique. But more importantly, since we are interested to examine whether the impact of explanatory variables on firm performance differs between top performing and bottom-performing firms, we apply panel quantile regression method. However, the study finds that ownership opacity as well as internal financial capital, both are responsible for improved performance of group-affiliated firms. This refutes institutional void theory. The findings are analyzed from the perspectives of Resource-Based View, Resource Dependency theory and agency theory.

8.1 Introduction One important feature of business or industrial organizations in most of the emerging economies is the ubiquitous presence of business groups. Business groups as defined by Khanna and Rivkin (2001) are “a set of firms which, though legally independent, are bound together by a constellation of formal and informal ties and are accustomed to taking coordinated action”. The ubiquity of the business groups and the critical role played by them in the emerging economies suggest that group affiliation may affect the performance of the affiliated firms positively or negatively depending upon the relative strengths of the benefits and costs associated with the group affiliation. This has attracted the researchers to examine the characteristics and the performance of these groups. In fact, there is not a dearth of studies related to business group literature J. Mukhopadhyay (B) Independent Researcher, Kolkata, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_8

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that examine the relationship between group affiliation and firm performance in the context of emerging economies. However, most of these researches have been carried during the period when the institutional setup was weak, external capital market was underdeveloped and factor markets were imperfect. In the post-1991 period, as a part of economic reforms, India started to adopt market-oriented reforms, which has brought a substantial transformation in the institutional landscape of the economy especially after the period 2000–2001 with the adaptation of corporate governance measures. This new institutional environment has created opportunities as well as challenges for both the group-affiliated and unaffiliated firms. On one hand, the firms have got the opportunities to grow by accessing larger market but on the other hand, they are required to accept new laws and regulations and withstand competition that might come from domestic as well as foreign firms. In fact, economic liberalization can have either a positive or negative impact on the performance of business groups. In the regulated regime of pre-liberalization era, group firms used to be benefitted by engaging themselves in unrelated diversification. However, in the post-liberalization period, those firms can also perform well by restructuring their businesses as per their core competencies. Even with the development of market institutions, group firms can still make use of the advantages that they used to have in the pre-liberalization period with respect to internal factor markets, other non-marketable factors, previous contract based on trust and their reputation as against the stand-alone firms to explore the opportunities that arise in the market due to liberalization (Khanna and Yafeh 2007). Business groups create a strategic network among the group members and share information, knowledge, technical know-how and resources that are not accessible to the outsiders. In most cases, these business groups have higher connections to political power that provide them wider opportunities. On the other side, the structures of business groups are complex in nature which gives rise to the organizational rigidities making it difficult for them to adjust to the new liberalized environment in comparison to the unaffiliated firms. Further, if group-affiliated firms did enjoy the benefits of being a group member in the regulated regime to such an extent that their performance far exceeded than that of the stand-alone firms, then it can also happen that performance differentials will be wiped out in the post-reform era which induces increased competition among firms (Sarkar 2010). In this respect, it is worth investigating the performance of stand-alone firms against that of the group-affiliated ones in Indian Manufacturing sector during the post-liberalization period. In addition to this, we also want to explore how far the group firm characteristics and group-level features are responsible for poor or better performance of group-affiliated firms. We have taken our span of study from 2000–01 to 2012–13. This is because corporate governance mechanism in India was introduced in the late 1990s as a major initiative by Confederation of Indian Industry (CII). Though it was considered as a voluntary measure, it was soon made a mandatory status in the early 2000s. However, thereafter, it was sometimes made voluntary and sometimes voluntary.

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India provides a particular study of interest to study the impact of group affiliation on firm performance for various reasons. One such reason is that although business groups in India emerged in pre-independence period it still rules the corporate sector besides playing a significant role in Indian economy. This scenario has remained unchanged although the institutional environment in India has undergone a radical transformation. Indian corporate sector is characterized by highly concentrated ownership and control structures where control in most cases is in the hands of a family. Another characteristic of Indian corporate sector is the coexistence of group-affiliated firms with a large number of stand-alone firms. These group affiliated companies that are connected by interlocking directorate as well as shareholders are controlled by listed holding companies, either single or multiple. In many instances, in absence of any identifiable holding company, promoters exercise their control over other affiliated companies using flagship company as a cornerstone through the subsidiaries, private companies as well as trusts where the family members are the majority stakeholders. The group-affiliated firms have a pyramid-like structure with holding or flagship company lies at the top of the pyramid. In such type of companies, promoters are the ultimate owners and have entire control of them since they are the maximum shareholders of those companies. As for the affiliated ones situated within the pyramid, the promoters of the holding companies exert informal influence over them without holding majority shares of those companies. Secondly, business groups in India were created as a strategic response to imperfections in the factor market at a time when external financial market was underdeveloped. Presently, India is a country with well-developed external market and strong institutional setup. The series of research in emerging economies suggest that both benefits and costs are associated with business group affiliation and it is not clear whether affiliation should be considered as “parasites” or “paragons” (Khanna and Yafeh 2007), “heroes or villains” (Claessens et al. 2000). There are several theories related to the impact of business group affiliation on firm performance. These theories are agency theory, institutional theory, transaction cost theory, resource-based theory and resource dependency theory. Institutional theory as propagated by North (1990) focuses on how organizational structure as well as behavior is influenced by the socio-cultural rules and values along with the laws and judicial system. According to North (1990), institutions bring stability in the structure of economic exchanges by reducing uncertainty through putting a restraint on the options available to both the individual and organizations. The cost of transactions depends on the effectiveness of institutions. In transaction cost theory, exchange of goods and services is managed by markets and organizations both of which act as a substitute mechanism of each other. The resource-based theory (Wernerfelt 1984; Barney 1991; Grant 1991) emphasizes on the firm-specific internal factors and their influence on firm performance. According to this theory, organizations are bundle of unique resources, the combination of which lead to organizational capabilities (Grant 1991) and help the firms to attain competitive advantage over others, the result of which is reflected on their improved performance. On the other hand, the resource dependence theory argues that firm tries to acquire resources from the external environment consisting of various groups and

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while doing so, the more firm interacts with the environment, the more it becomes assure about its access to resources and more it becomes dependent on the source of resources (Pfeffer and Salanick 2003). Reduction in resource uncertainty helps to improve firm performance. The studies that find a positive relationship between group affiliation and firm performance (Khanna and Palepu 2000; Khanna and Rivkin 2001) argue that transaction cost theory and institutional theory are complement to each other. In emerging economies, while institutional theory indicates market failures or market imperfections in capital, labor and product market with underdeveloped external market, transaction cost theory suggests that group-affiliated firms take advantage of this market failure by internalizing the transactions within the business groups and creating a value-producing synergy of internal network both of which lead to the reduction of transaction cost. Hence, in case of institutional voids and market failures, business groups by serving as a substitute outperform the standalone firms. Moreover, from the perspective of resource-based view, business group-affiliated firms have more access to group resources which they can avail easily. Moreover, affiliated firms have the advantages of sharing the information which they can exploit in allocating resources among units (Williamson 1967). Summarizing the above argument, it can be said that as long as the internal market is more efficient than the external market, the benefits associated with group affiliation are more than the costs of group affiliation (cost to be incurred for transparency). In such a case, irrespective of whether the affiliated firms are transparent or not, they generally outperform the stand-alone firms. On the other side, there are studies that find a negative impact of business group affiliation on firm performance (Claessens et al. 2000). This negative relation between group affiliation and firm performance can be explained with the help of agency theory. According to the agency theory, agency problems between controlling shareholders or owners and minority shareholders arise due to the disparity in the interests of group controlling owners and minority investors of each group. For example, as against the profit maximization objective of investors of individual affiliated firms, the group controlling owners would try to focus on the growth of the whole group and share risk among affiliated firms at the expense of profits of the affiliated firms. A more severe agency problem is the expropriation of minority shareholders by the controlling owners. This phenomenon is known as tunneling, which causes diversion of profit from the group-affiliated firms where the controlling shareholders have low cash flow rights to those where they have high cash flow rights (Johnson et al. 2000; Bertrand et al. 2002). This leads to decline in the performance of the group-affiliated firms because of cross-subsidization and increased possibilities in mutual entrenchment (Claessens et al. 2002; Morck and Yeung 2003). The business groups would fail to take optimal decision and the market perception would lead to the decrease in the value of group firms. Hence, if the agency problem is prevalent, then it is expected that group-affiliated firms would perform worse than that of the stand-alone firms. In such a situation, in order to hide the expropriation, group firms would prefer to be less transparent than the stand-alone firms.

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However, this scenario might change if the external markets, particularly capital market are well developed. In fact, the liberalization program has thrown up a challenge to the group-affiliated firms. This is because relative benefits of the internal markets in comparison to the external markets is rapidly disappearing from the market. An adoption of strong institutional environment has created an atmosphere for the external market especially the capital or financial market to work efficiently in the way that was never imaginable before. If the group firms want to take the benefits of the external market to obtain resources from the market, they have to incur additional costs to be transparent. The well-developed external market also results in the efficient monitoring from outside. The adoption of corporate governance mechanisms, either mandatorily or voluntarily leads to greater transparency of the firms. With the increase in transparency, agency problems diminish. Hence, if the transparency of the group-affiliated firms is higher, and then group firms are expected to perform better than the unaffiliated ones. This is because better transparency of the firms will not only reduce the cost of acquiring external resources but also increase the valuation of the firms. Further, group-affiliated firms also enjoy the advantages of group synergy effects which help in better performance of firms. In this study, we try to examine whether any of the above arguments are suitable for explaining the comparative performance of group-affiliated firms as against the stand-alone firms. We not only try to find out whether the group-affiliated firms exhibit better performance than the stand-alone firms but also attempt to figure out the factors that are responsible for group-affiliated firms to perform better or worse than the stand-alone firms. The earlier studies have attempted to focus on one or the other features of business groups in order to examine the impact of business group on firm performance. For example, there are studies (Yiu et al. 2005; Chang 2006; Langlois 2013) that consider evolutions of business groups to examine the influence of group affiliation on firm performance. On the other hand, Morck and Yeung (2003), Cainelli and Iacobucci (2011) consider ownership and control patterns as the characteristics of business groups in their studies. The other aspects of business groups that have been studied by the past literatures are access to different resources like capital (Encarnation 1989; Amsden and Hikino 1994) and group diversification and internationalization (Nayyar 1993; Guillén 2003). Further, most of the studies pertaining to emerging economies are mainly cross-sectional in nature (Khanna and Rivkin 2001; Singh and Gaur 2009). In this study, apart from considering both the objectives, mentioned above, we analyze on the basis of panel data. Moreover, we try to examine how different factors affect the firm performance at different levels of firm performance. This will help us to know whether the factors affecting the topperforming firms are also affecting the bottom-performing firms in the same way or in a different way. Our analysis is based on 14,274 BSE-listed manufacturing firms, out of which 6565 numbers are group affiliated and 7709 numbers are stand-alone. Our period of study spans from 2000–01 to 2012–13. By applying dynamic panel data regression technique, we find that group-affiliated firms outperform the stand-alone firms irrespective of whether the performance is measured by Tobin’s Q or ROA. Moreover, in order to find out which of the factors are responsible for better performance

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of group-affiliated firms, we again apply dynamic panel data regression estimation procedure. However, this time, we have considered only group-affiliated firms for analysis. Excluding those firms for which all the required information is not available, we end up with 3341 number of group-affiliated firms. Further, in order to find whether the factors affecting the performance of top-performing firms are also affecting the performance of the bottom performing firms in a similar way or not, we employ panel quantile regression method. We find that apart from age and size of the firms, ownership opacity positively influences firm performance when performance is measured by Tobin’s Q. On the other hand, when performance is measured by ROA, we get that age, ownership opacity and financial capital exhibit a positive impact on firm performance. The rest of the paper is structured as follows. Section 8.2 presents the methodology considered in this study. In Sects. 8.3 and 8.4, we explain the data and the variables selected for our study respectively. Section 8.5 presents the analysis of our findings, and Sect. 8.6 concludes.

8.2 Methodology 8.2.1 Performance of Group-Affiliated Firms as Against Stand-Alone Firms Our first objective is to find out how the group-affiliated firms perform as against the stand-alone firms. We apply dynamic panel data regression technique which addresses the endogeneity issue present in the model. In our case, the use of dynamic panel data regression model is appropriate because the dependent variable is affected by its own past realizations (Bond 2002), which indicates the presence of endogeneity problem in the model. Our model is as follows: Yit = α1 Yit−1 + β1 G R OU Pit + β2 X it + ηi + λt + εit .

(8.1)

where i = 1,…., N and t = 1,…., T; i denotes firm and t denotes time period or year. Moreover, Yit is the performance variable measured by Tobin’s Q and ROA. While the variable ηi indicates firm-specific fixed effects, λt captures time effects. Both of them are assumed to be fixed parameters. Xit are the control variables and εit is the error term with zero mean and constant variance and assumed to be uncorrelated across N and t. GROUPit is an explanatory variable. It is also a dummy variable that takes value 1 when a particular firm is affiliated with the group and 0 otherwise. Further, even in the absence of auto-correlation between the predictor variables and the error term, there is a possibility of the lagged dependent variable present in the above equation to be correlated with the unobserved heterogeneity. We also

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assume that reverse causality exists which arises from potential endogeneity of lagged dependent variable. In order to estimate (8.1), we have to get rid of the firm fixed effects from the equation and this we can do by first differencing. Hence, we get, Yit − Yit−1 =α1 (Yit−1 − Yit−2 ) + β1 (G R OU Pit − G R OU Pit−1 ) + β2(X it − X it−1 ) + (λt − λt−1 ) + (εit − εit−1 ).

(8.2)

Alternatively, /Yit = α1 /Yit−1 + β1 /G R OU Pit + β2 /X it + /λt + /εit .

(8.3)

Since (8.3) is dynamic in nature, the variables Yit and Yit−1 are correlated with each other. In order to solve this problem, Anderson and Hsiao (1982) suggested the use of /Yit−2 orYit−2 as instruments for /Yit . In fact, endogenous variables with three or more period lags can be considered as instruments (Holtz-Eakin et al. 1988). Arellano and Bond (1991) suggested a technique that utilizes all possible instruments. They use the Generalized Method of Moments (GMM) and by the use of those moments conditions that are generated by the lagged levels of dependent variables (Yit−2 , Yit−3 ,….) with/Yit−1 , they got the estimates that are known as difference GMM estimators. Moreover, extending this technique of Arellano-Bond, Arellano-Bover/Blundell-Bond developed an estimator, which requires an additional assumption that the fixed effects and the first differences of instrumental variables are uncorrelated with each other. This gives rise to the requirements of additional instruments and this also enhances efficiency (Roodman 2009). It gives rise to the development of a system of two equations (the original equation and the transformed one), which is popularly known as system GMM. In this study, we employ a linear dynamic panel data (DPD) regression technique. This method is developed on the basis of both ‘difference-GMM’ of Arellano and Bond (1991) and ‘System GMM’ of Arellano-Bover (1995), Blundell-Bond (1998) estimation procedures. In order to tackle standard error bias, we employ Windmeijer two-step robust standard error estimation process. With large cross-sectional observations (N) and small time period, the use of dynamic panel data estimation leads to the production of consistent estimators. In our study, it is appropriate to use dynamic panel data estimation technique because N is much larger than T. Also, for studying the second objective, i.e. to determine the factors responsible for better or worse performance of group-affiliated firms, we employ dynamic panel data regression technique too in order to address the endogeneity issue associated with the presence of lagged dependent variable as an explanatory variable in the model. However, in this case, we only consider the group-affiliated firms and the control variables are different from those which we have taken in (8.1). The model when we consider only group-affiliated firms is as follows: ' Yit' = α1' Yit−1 + β1' X it' + β2' Z it' + ηi' + λ't + εit' .

(8.4)

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where Y' it is the performance variable measured by Tobin’s Q and ROA.X' it s are explanatory variables, Z' it s are control variables, η' i is firm-specific fixed effects, λ' t is time effect and ε' itn is the error term.

8.2.2 Impact of Different Factors on the Performance of Group-Affiliated Firms Since we are interested in whether the impact of explanatory variables on firm performance differs between top-performing and bottom-performing firms, we apply panel quantile regression method. Application of quantile regression estimation helps to estimate the slope coefficients (different attributes of group-affiliated firms) at different quantiles or percentage points of the relevant distribution which in our case is firm performance. Since panel quantile regression method allows unobserved heterogeneity, this measure helps to explore differences in the performance level among low, moderate and high-performing firms. In this study, we apply a dynamic quantile regression model which takes into consideration the impact of past firm performance. The dynamic quantile panel regression in our case is as follows: ' QYit' (τ ) = α1' (τ )Yit−1 + β1' (τ )X it' + β2' (τ )Z it' + ηi' + εit' .

(8.5)

In this case, the impact of Y' it−1 , X' it s and Z' it depends on the τth quantile of interest. The other notations and symbols have already been described before. The parameter estimates on the lagged dependent variable changes along the different quantiles. There are various methods by which quantile dynamic panel fixed effects can be estimated (Koenkar 2004). However, those methods can give biased estimates in case time dimension is not sufficiently large. In order to address the endogeneity problem in the presence of lagged dependent variable in (8.5) we apply Quantile-Regression-Instrument-Variable (QR-IV) as suggested by Galvao (2011). Motivated from the work of Chernozhukov and Hansen (2005), Galvao (2011) proposes that the dynamic bias can be reduced by the application of instrumental variable quantile regression method. The method developed by Galvao (2011) is a combination of dynamic panel data regression method and quantile instrumental variable technique. However, the key advantage of using this method is that in this approach, any transformation of the model is not required. As suggested by Galvao (2011), we use the lagged values of dependent variable as instruments to estimate (8.5).

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8.3 Data Our study is based on BSE-listed firms collected data from PROWESS database of CMIE (Centre for Monitoring Indian Economy Pvt. Ltd.). The period of study spans from 2000–01 to 2012–2013. Our first objective is to find out the relative performance of group-affiliated firms as against the stand-alone firms. For that, our analysis is based on balanced panel data comprising of 14,274 numbers of firms. Further out of 14,274 numbers of firms, 6565 numbers are group-affiliated firms as against 7709 number of stand-alone firms. In order to find out the factors responsible for positive or negative performance of group-affiliated firms as against the stand-alone firms, we separately analyze the group-affiliated firms. We have excluded those group-affiliated firms from our study for which we do not have required information on opacity and wedge which are important for explaining group-firm characteristics. Hence, excluding those firms, finally analyze the model based on 3341 number of observations.

8.4 Key Variables of the Study 8.4.1 Dependent Variable We employ Tobin’s Q and Return on Assets (ROA) as two measures of firm performance. Based on accounting information, ROA is a backward-looking method that captures the historical performance of the firm. On the other hand, values of Tobin’s Q indicate the expected future performance of the firm since the measure is based on stock market price. It is considered as a forward-looking measure. Following the studies of Khanna and Palepu (2000) and Sarkar and Sarkar (2000), we calculate Tobin’s Q as. Tobin’s Q = (market value of equity + book value of total liabilities) /book Value of the Assets; ROA is measured as the ratio between a company’s earnings before interest and taxes (EBIT) to its total assets.

8.4.2 Explanatory Variables Performance of group-affiliated Firms vis-à-vis stand-alone firms GROUPD, for the first sub-objective, GROUPD is a dummy variable that indicates whether the particular firm is a group affiliated or not.

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Impact of Different Factors on the Performance of group-affiliated Firms In order to find out the reasons behind poor or better performance of group-affiliated firms as against the stand-alone firms, we consider the effect of group-affiliated firm characteristics and group-level characteristics on firm performance. group-affiliated firm characteristics In order to capture the group-affiliated firm characteristics, we take wedge (ownership disparity between the control rights and cash flow rights) and ownership opacity as variables. These are two main variables that can serve as a proxy for incentives to tunneling (Kali and Sarkar 2011). Wedge (WEDG), The pyramidal or circular ownership structure gives rise to ownership disparity, which is considered as a main source of principal–principal agency problems because controlling owners have the possibility to increase their wealth by diverting resources from the firms where they have lower cash flow ownership to those firms with higher cash flow ownership (Johnson et al. 2000). The insiders of Business Group by various means can expropriate the wealth of the other shareholders. One such way is to transfer capital from one firm to another firm despite the fact it may not serve the interests of the other stakeholders. This phenomenon is known as tunneling (Johnson et al. 2000). This occurs when there is a wedge between cash flow rights and control rights. The pyramidal or circular ownership structure gives rise to ownership disparity, which is considered as a main source of principal–principal agency problems because controlling owners have the possibility to increase their wealth by diverting resources from the firms where they have lower cash flow ownership to those firms with higher cash flow ownership (Johnson et al. 2000). If firms where insider ownership is high show a tendency of obtaining or retaining more capital, then it indicates that those firms are trying to have a control over the capital formation. This suggests a case of expropriation. Wedge of a firm is defined as the difference between the control rights and the cash flow rights of the controlling insiders. In case of a particular affiliate, a direct ownership holding of the controlling insiders in that affiliate is considered as the cash-flow rights. On the other hand, control rights are considered as the sum total of percentage of equity holdings by the controlling insiders and by other group-affiliated firms in the same affiliate. In India, so far, two proxy measures for wedge have been used in the literature of business groups. Kali and Sarkar (2011) have considered the percentage of outstanding shares held by persons acting in concert (PACs) as a measure of wedge. However, data on PACs are not available in Prowess in the post-2005–06 period. Another proxy measure of wedge, which has been employed by George et al. (2008), is the percentage holdings of outstanding shares by non-promoter domestic corporations. We use this measure in our study. According to them, shareholdings by domestic corporations indicate the control of the family over an affiliate, which is exercised mainly through the other group-affiliated firms in a group. Opacity (OPAC). Another variable of interest that is also responsible for creating agency problem is ownership opacity. It is based on the proposition that ownership

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stakes of the controlling owners are not always completely disclosed in the public domain. The motive to stay opaque (ownership) can be described with the help of two competing hypothesis. One is entrenchment hypothesis, which suggests that controlling owners want their firms to stay opaque since it helps them to entrench their objective of expropriating firm resources. The other one is monitoring hypothesis, according to which family owners or controlling owners are efficient in inside monitoring and hence they do not require to be transparent as such because the costs of transparency in their case may be more than that of the benefits they would receive for being transparent. In the presence of agency problem in a firm, it becomes difficult for an outsider to understand the differences and the relationship between ownership and control in that firm. In addition to the complexity of ownership structure, one significant source of agency costs in case of Indian listed firms is the opacity of ownership structure (Sarkar 2010). As identified by Sarkar (2010), the determinants of ownership opacity in the Indian perspective can be of three types—the identity of the owners is not disclosed completely (Type I), the insider ownership is fragmented among a large number of owners (Type II) and the degree at which ownership is controlled by private bodies (Type III). Between 2002 and 2006, as per the disclosure regulations, the identity of only those equity owners having at least 1% of equity ownership were required to be disclosed by the Indian listed firms. Hence, in order to avoid mandatory disclosures, there might be a tendency among the controlling shareholders to keep the insider ownership strategically and deliberately below 1%. The higher the percentage of shareholding fall in this below 1% category, more will be the opacity of ownership structure from the perspective of an outsider. This type of opacity is known as Type I opacity. Type II opacity arises when a given shareholding is distributed or fragmented among a large number of insiders. On the other hand, Type III opacity occurs when the promoters’ shareholding is weighted more towards the unlisted companies and trusts in comparison to the listed companies. In such a case, it becomes difficult for the outside minority shareholders as well as the outside members of the board of directors to understand the chains of control and any related party transactions. In this study, we have concentrated only on Type II opacity. This is because, in the post-2006, the changed regulations compel the firms to disclose the identity of all the promoters and the promoter group as well as their respective shareholdings under clause 35. Hence, Indian-listed firms are now almost free from Type I problem. We have also not taken into consideration Type III opacity because it is hard to compute for all the listed firms due to the limitations of data. Type III opacity is calculated as the ratio of total percentage of shareholders to total number of promoters. Group level characteristics Group Size (GSIZE) The bigger groups can have a positive impact on the performance of the member firms as these groups have the capabilities to access resources easily and hence are more efficient in allocating resources. They also enjoy economies of scale that lead to the reduction of cost (George et al. 2008).

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Diversification (GDIV) It could be advantageous for the group firms if the group can profitably utilize its resources like managerial skills, technical know-how etc. to those industries in which it operates. Nevertheless, group size and group diversification can have a negative impact on firm performance if the wealth creation and excessive risk aversion are the motives behind diversification. From the perspective of agency theory, the managerial interests at the costs of shareholders lead to firm diversification. Internal capital markets are more likely to be well developed for bigger and diversified business groups in comparison to the smaller and less diversified groups. While it is implicit that the firm undertakes diversification as a strategy to grow and maximize profits, it is often not very explicit why the firm chooses to do so. According to the market power theory, the firms diversify in order to dominate the market (Martin and Sayrak 2003; Montgomery 1994) and in order to do so, they want to eliminate the small competitors by aggressive pricing which is backed by utilization of cash flow generated in other business units. Montgomery (1994) and Martin and Sayrak (2003) recognize three theories that help to explain the motivation of a firm to diversify its businesses. These three theories are agency theory, resource-based theory and market power theory. From the perspective of agency theory, the decision of the firm to diversify is based on opportunistic reasons (Jensen 1986; Jensen and Meckling 1976; Shleifer and Vishny 1989). The managers, which in our case, are the controlling shareholders look for private benefits and hence go for firm diversification at the cost of minority shareholders. Thus, according to the agency theory, diversification aggravates the opportunistic problems. This explains the negative impact of diversification on firm performance in terms of profit and market value. In fact, many studies find a negative relationship between diversification and firm performance (Lang and Stulz 1994; Berger and Ofek 1995; Denis, Denisand Sarin 1997). However, according to Aggarwal and Samwick (2003), there is another argument related to agency theory that can explain the motivation for corporate diversification. Extending the argument of Aggarwal and Samwick (2003) with respect to Type I agency problem to Type II agency problem, it can be said that the controlling shareholders go for unrelated diversification to reduce idiosyncratic risk. From the point of resource-based view, diversification takes place when the firms have surplus resources and capabilities which can be moved from one industry to another (Mishra and Akbar 2007). According to Chatterjee and Wernerfelt (1991), while resources like physical, knowledge-based and external finance are linked to related diversification, ‘internal financial resources’ which ensure availability of long-term capital is related to unrelated diversification. Internal capital market theory suggests that a firm can operate efficiently if it has the ability to transfer capital generated in one unit to another. Myers and Majluf (1984) suggest that the extent of asymmetric information problems is often found to be less critical for diversified firms. Further, as suggested by Matsusaka and Nanda (2002), coinsurance takes place when the firms as a result of diversification are able to reduce the cash flow variations and then succeed in decreasing the probability of being insolvent. This helps them to get loans at a lower cost in comparison to

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focused firms. Hann et al. (2013) suggest that coinsurance effect has the capability of decreasing the systematic risk in diversified firms. This reduces their cost of capital, making diversified firms attractive for investment. Since diversification in our study is a proxy variable for tunneling, we measure the diversification, following the measure adopted by Kali and Sarkar (2005) based on weighted index of diversification (Caves et al. 1984). Since we are interested in measuring the diversification of a group-affiliated firm in terms of relatedness to the core activities of the group, we adopt the discrete measure, which is based on the International Standard Industrial Classification (ISIC) developed by the United Nations. In line with the ISIC code, National Industrial Classification (NIC) code has been developed in India in such a way that it is equivalent to ISIC code. The activity of each firm in the Prowess database has been assigned a NIC code up to 4-digit level. Our measure of diversification captures the extent to which an activity of a group-affiliated firm is deviated from the group’s core competencies to unrelated diversification. Unlike other studies where this concept of relatedness is applied in case of a firm engaged in various activities, we follow Kali and Sarkar (2005) in our study and apply this concept in case of a group consisting of various firms. Since each firm belonging to a group is associated with a single activity; it has been assigned a particular NIC product code at the 4-digit level as a single segment firm. The main activity of the group is determined by the NIC4 of the core firm and the diversification of a firm is measured by the distance by which its activity is away from the core firm’s activity in the group divided by the assets of the firm. Following Caves et al. (1984), let us define the distance dijk for the ith firm of jth group involved in the kth activity at the 4-digit level of NIC code in such a way that dijk takes the value zero if the ith firm’s 4-digit NIC code is same as that of the core firm, dijk is one if the firm belongs to the same 3-digit industry but in a different 4-digit industry as that of the core firm,2 if the firm belongs to a different 3-digit industry but within the same 2-digit industry and finally 3 if the activity of the ith firm is in that 2-digit industry which is different from that of the core firm. If by unrelated diversification, the groups can potentially tunnel out funds from firms engaged in core activities to firms engaged in unrelated activities, then the above measure can capture the relationship between a group-affiliated firm’s relative positions in the ownership period with that of the degree at which the firm’s production activity is close to the core activity of the group. The firm’s relative position in the ownership period is determined on the basis of the divergence between ownership and control rights. The higher is the firm’s position in the ownership pyramid, the lower will be the wedge and more it will be located way from the core activities of the business group. Let us define distijk as a discrete variable that takes either one of the nominal values 0,1,2,3. Depending on the relatedness of the activity of the core, each group-affiliated firm take either one of the above values. Distijk = 0 if k belongs to the same 4-digit activity as that of the core firms but in a different 3-digit activity. To explain this, Caves et al. (1984) have considered an example of n number of firms with n = 4 and firms are named as A, B, C, D which are engaged in m number

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of distinct/different activities (m = 4). They denote these activities as p, q, r and s, respectively. Let. P be the activity taken y group-affiliated firm A, and it is also the core activity of the group and A holds the highest proportion of total group. Inside Financial Institution/Internal Financial Market An internal capital market has both advantages and disadvantages over external capital market. From the positive side, internal market has greater information about investment prospects (Myers and Majluf 1984) and can add value by providing efficient monitoring (Jensen and Meckling 1976). On the negative side, internal market often led to cross-subsidization (Rajan et al. 2000; Shin and Stulz 1998), which can have a negative impact on firm performance. In order to capture the phenomenon that a group can make use of the inside financial market for investing in diversified activities when capital market is not fully developed, we have taken a variable named Inside Financial Resource (IFR). Within a business group, IFR acts as a proxy for an internal capital market. Following Chatterjee and Wernerfelt (1991), we calculate IFR as group’s current assets to its current liabilities. When a group-affiliated firm is involved in inter-corporate financing as well as investing, it helps in retaining and hence reallocating capital within the same business group. However, cross-subsidizing poorly performing firms at the cost of wellperforming firms by use of internal capital market can have a negative impact on firm performance (Meyer et al. 1992).

8.4.3 Control Variables SIZE is measured by log (assets) to capture the size of the firm. AGE is log(age) to measure the firm’s age. LEV is leverage which is measured by total debt to total assets. However, when we consider only the group-affiliated firms, we take control variables as SIZE and AGE.

8.5 Empirical Analysis From the descriptive statistics, it is clear that the average values of Tobin’s Q and ROA of group-affiliated firms are slightly greater than that of the stand-alone firms. VIF factor makes it clear that the model does not suffer from any multicollinearity problem (Table 8.1). Performance of group-affiliated Firms vis-à-vis stand-alone Firms Our dynamic panel data regression model is as follows: Yit =α1 Yit1 + β1 G R OU Pit + β2 S I Z E it + β3 AG E it

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Table 8.1 Descriptive statistics for all firms Observations

Mean

Standard deviation

Minimum

Maximum

Stand-Alone TOBIN’S Q

7709

1.399751

0.671566

1.001784

14.549

ROA

7709

0.144738

0.147105

−4.1579

1.049935

SIZE

7709

1.475442

2.186051

12.97805

AGE

7709

6

123

LEV

7709

0.467258

0.695075

0.000021

15.82006

TOBIN’S Q

6565

1.515064

0.785656

1.001299

11.18976

ROA

6565

0.153013

0.134702

−0.67332

1.438912

SIZE

6565

1.651734

2.587764

14.97866

AGE

6565

1

150

LEV

6565

0.429556

0.392717

6.24E-07

5.928241

TOBIN’S Q

14,274

1.452787

0.728513

1.001299

14.549

ROA

14,274

0.148544

0.141591

−4.1579

1.438912

SIZE

14,274

1.829249

2.186051

14.97866

AGE

14,274

1

150

LEV

14,274

6.24E-07

15.82006

6.344446 26.09949

16.75298

Group-Affiliated

8.264547 37.1802

21.42775

ALL

7.227553 31.19581 0.449918

19.82995 0.576359

Source Author’s calculations

+ β4 L E Vit + ηi + λt + εit

(8.6)

where Yit indicates Tobin’s Q and ROA in two different models, respectively (Table 8.2). Our findings from the linear dynamic panel data regression suggest that groupaffiliated firms have outperformed the stand-alone firms irrespective of whether the performance is measured by Tobin’s Q or ROA. Our results apparently support the findings of Khanna and Palepu (2000) and refute the findings of Claessens et al. (2000). There may be various reasons for the group firms to perform better than the stand-alone firms. Affiliation to business group has both positive and negative attributes. According to Khanna and Palepu (2000), one of the reasons for group firms to perform better is the efficiency of internal market in the absence of welldeveloped external capital market. However, whether their argument is still valid in the country where institutional environment has undergone a sea-change still remains a question. In case of market failures in developing countries, group-affiliated firms make use of the internal capital market. On the other hand, if with the development of external financial market, the transparency of the group-affiliated firms increases so that they can access the external resources at a lower cost, then it is also possible that group-affiliated firms exhibit a better performance than stand-alone firms.

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Table 8.2 Panel data regression estimates for all firms

Tobin’s Q

ROA

SIZE

−0.614*** (0.140)

−0.117*** (0 0.021)

AGE

0.062*** (0.014)

0.006* (0.003)

LEV

−2.932*** (1.065)

0.343*** (0.084)

GROUPD

4.141*** (1.303)

0.176*** (0.023)

CONS

3.117*** (0.922)

0.565*** (0.056)

AR(1)

−1.116

−1.677

AR(2)

−0.5825

−0.961

Source Author’s calculations Note (i) Figures in parentheses are standard errors (ii) * implies significant at 1% level (iii) ** implies significant at 5% level (iv) *** implies significant at 10% level

In order to find out which of the factors are responsible for better performance of group-affiliated firms, we run a separate panel-data regression for group-affiliated firms, the results of which have been analyzed in the subsequent sections. The control variables indicate that matured but smaller firms are better performers as against the newer and bigger firms. Further, while leverage has a positive and significant impact on firm performance measured by ROA, it has a negative and significant impact on Tobin’s Q. The post-estimation results indicate the absence of serial correlations in the model. This signifies that the model is correctly specified. Impact of different factors on the performance of group-affiliated firms Dynamic Panel data regression model for this objective is as follows: ' Y ' it =α1' Yit−1 + β1' G S I Z E it + β2' O P ACit + β3' W E DGit + β4' it + β5' AG Eit + β6' S I Z Eit + ηi' + λ't + εit'

(8.7)

where Y' it indicates Tobin’s Q and ROA in two different models (Table 8.3). The results from linear dynamic panel data regression model from the coefficients associated with size and opacity, all other coefficients are insignificant when performance is measured by Tobin’s Q. We find that both the size and the opacity have a positive and significant impact on firm performance when Tobin’s Q is the measure of firm performance. On the other hand, when performance is measured by ROA, we find that the variables like AGE, and GSIZE have a negative and significant influence on firm performance. However, SIZE has a positive and significant impact on ROA. The post-estimation results show that the model is not mis-specified, which is

8 Differences in the Performance of Group-Affiliated and Stand-Alone Firms

223

Table 8.3 Dynamic panel data regression estimates for group-affiliated firms Tobin’s Q

ROA

AGE

−0.0068083(0.0083467)

−0.0044528*(0.0015685)

SIZE

0.3687163*(0.0648605)

0.0636842*(0.0154625)

GSIZE

−1.16e-06(1.12e-06)

−2.36e-06*(8.73e-07)

OPAC

0.0119743***(0.0069002)

0.0003893(0.0004865)

WEDG

0.0033615(0.0039272)

−0.0017075(0.0012126)

IFR

0.0521213(0.0664182)

−0.0035358(0.0088228)

CONS

−1.354649(0.5308828)

−0.1299247(0.1111182)

AR(1)

−2.4967***

−1.0327

AR(2)

−0.23816

−0.97291

Source Author’s calculations Note (i) Figures in parentheses are standard errors (ii) * implies significant at 1% level (iii) ** implies significant at 5% level (iv) *** implies significant at 10% level

evident from insignificant AR(2) both in the cases when performance is measured by Tobin’s Q and ROA. Thus, dynamic panel data regression model fails to provide any significant insights about the positive influence of the factors considered in the model. In order to find out how these factors affect the firm performance and whether these factors at all can influence the firm performance at different levels, we apply panel quantile regression method and find that the results from the panel quantile regression method are somewhat different from the ones we got from the dynamic panel data regression method. The model for panel quantile regression for our study is as follows: ' QYit' (τ ) =α1' (τ )Yit1 + β1' (τ )G S I Z E it' + β2' (τ )G D I Vit' + β3' (τ )O P ACit' + β4' (τ )W E DG it' + β5' (τ )I F Rit' + β6' (τ ) AG E it + β7' (τ )S I Z E it' + ηi' + εit'

(8.8)

where Y' it indicates Tobin’s Q and ROA in two different models (Tables 8.4 and 8.5). It is clear from the results of quantile regressions that at most of the quantiles, factors responsible for positive performance of firms when performance is measured by Tobin’s Q are past performance of the firm in terms of Tobin’s Q, AGE and SIZE of the firms and opacity. These indicate that matured and bigger firms are expected to show better performance in comparison to newer and smaller firms. However, AGE has a significant impact on ROA at 0.40 and 0.80 quantiles. On the other hand, when performance is measured by ROA, the variables that have positive impact on firm performance at most of the quantiles are past performance of the firm in terms of ROA, age, opacity and internal financial capital.

0.61577* (0.0183)

0.00060 (0.0018)

−2.50e-08 (7.28e-08)

0.00104* (0.0003)

−0.00027 (0.00029)

0.00006 (0.00056)

0.4690* (0.025)

0.00019 (0.000)

0.0015 (0.002)

−4.24e-08 (1.02e-07)

0.000341 (0.00193)

0.00100* (0.000)

−0.00039 (0.000)

−0.000166 (0.000)

0.508397* (0.028)

AGE

SIZE

GSIZE

GDIV

OPAC

WEDG

IFR

CONS

0.2737* (0.0226)

0.00018 (0.0005)

−0.00148 (0.000)

0.00128* (0.000)

0.000699 (0.002)

−7.55e-08 (7.32e-08)

0.00070 (0.0018)

0.00018 (0.000)

0.70957* (0.0175)

0.30

0.17900* (0.0236)

0.001452 (0.000)

−0.00006 (0.000)

0.00189* (0.0001)

0.0009 (0.002)

−1.24e-07(8.06e-08)

0.00172 (0.002)

0.00025*** (0.000)

0.79439* (0.0018)

0.40

0.09694* (0.0214)

0.000069 (0.000)

−0.00010 (0.000)

0.00219* (0.000)

0.00045 (0.002)

−1.36e-07 (9.20e-08)

0.00386** (0.002)

0.00026 (0.000)

0.8686* (0.0182)

0.50

0.0068 (0.0286)

0.00014 (0.000)

−0.000128 (0.000)

−0.00078 (0.001) −0.000778* (0.0468)

−0.1185 (0.0354)*

0.00029 (0.001)

0.0055* (0.0014)

−0.0022 (0.005)

2.33e-07 (3.48e-07)

0.00967** (0.0047)

0.00084** (0.000)

1.1869* (0.0330)

0.80

−0.00026 (0.000)

0.0004 (0.000)

0.0037* (0.000)

0.007 (0.0032)

−0.00049 (0.0024) 0.00296* (0.000)

−2.14e-07 (2.37e-07)

0.0064** (0.003)

0.0002 (0.0002)

1.0853* (0.028)

0.70

−2.10e-07 (1.33e-07)

0.0043** (0.002)

0.0002 (0.000)

0.96567* (0.023)

0.60

Source Author’s calculations Note (i) Figures in parentheses are standard errors (ii) * implies significant at 1% level (iii) ** implies significant at 5% level (iv) *** implies significant at 10% level

0.36930* (0.0238)

0.0003 (0.002)

0.00018 (0.000)

20

10

TQ1

Table 8.4 Panel quantile regression results for affiliated firms when performance is measured by Tobin’s Q

−0.3145 (0.095)

0.00248 (0.0171)

−0.001 (0.001)

0.0084** (0.003)

0.005 (0.011)

4.85e-07 (4.38e-07)

0.0061 (0.010)

0.0009 (0.001)

1.398* (0.040)

0.90

224 J. Mukhopadhyay

0.0034* (0.0010)

−5.52e-08** (3.27e-08)

−0.00028 (0.001)

0.00017** (0.000)

−0.00037 (0.0002)

0.000637* (0.000)

−0.0472* (0.0097)

0.000017 (0.000)

0.00758* (0.001)

−1.07e-07* (3.15e-08)

−0.0003 (0.002)

0.00029** (0.000)

−0.000735*** (0.004)

0.00076* (0.000)

−0.09680* (0.0141)

AGE

SIZE

GSIZE

GDIV

OPAC

WEDG

IFR

CONS

0.30

−0.0188* (0.0066)

0.000657* (0.000)

−0.00008 (0.000)

0.000156** (0.000)

−0.00056 (0.001)

−2.75e-08 (2.06e-08)

0.0141** (0.0006)

0.0007 (0.000)

0.8619* (0.0143)

0.40

−0.00370 (0.007)

0.00055* (0.000)

−0.0000326 (0.000)

0.00021** (0.000)

−0.000246 (0.001)

−2.92e-08 (2.03e-08)

0.000267 (0.000)

0.000074 (0.000)

0.8954* (0.0139)

0.50

0.60

0.0145** (0.007)

0.00051* (0.000)

0.0000378 (0.000)

0.00023** (0.000)

−0.0001659 (0.000)

0.3277* (0.008)

0.00044* (0.000)

−0.0000766 (0.000)

0.00029* (0.000)

−0.00055 (0.000)

−8.39e-09 (2.08e-08)

−0.00208* (0.001)

−0.000896 (0.000) −1.85e-08 (1.70e-08)

0.000125** (0.000)

0.9273* (0.014)

0.000060 (0.000)

0.91633* (0.015)

0.70

0.0490 (0.008)*

0.000218** (0.000)

−0.00016 (0.000)

0.00033* (0.000)

3.62e-06 (0.000)

−1.19e-08 (2.51e-08)

−0.00257* (0.000)

0.000128** (0.000)

0.92859* (0.0134)

Source Author’s calculations Note (i) Figures in parentheses are standard errors (ii) * implies significant at 1% level (iii) ** implies significant at 5% level (iv) *** implies significant at 10% level

0.000083 (0.000)

0.20

0.829* (0.017)

0.10

0.76805* (0.0209)

ROA1

Table 8.5 Panel quantile regression results for affiliated firms when performance is measured by ROA 0.80

0.748* (0.0104)

0.000055 (0.000)

−0.000 (0.000)

0.0003** (0.000)

0.00108 (0.0012)

1.11e-09 (2.77e-08)

−0.0038* (0.001)

0.00008 (0.000)

0.94100* (0.0142)

0.90

0.1265* (0.151)

−0.00003 (0.0016)

0.000047 (0.000)

0.00045** (0.000)

0.0012 (0.0017)

4.40e-08 (6.18e-08)

−0.00698* (0.001)

0.0001 (0.000)

0.9455* (0.016)

8 Differences in the Performance of Group-Affiliated and Stand-Alone Firms 225

226

J. Mukhopadhyay

The results do not indicate much difference between the top- and bottomperforming firms with respect to the factors affecting firm performance. However, for the top-performing firms, size has a negative impact on performance whereas it has a positive impact on performance for the bottom-performing firms when performance is measured by ROA. As for the group firm characteristics, the findings suggest that opacity has a positive and significant impact on firm performance irrespective of whether the performance is measured by Tobin’s Q or ROA. This indicates that monitoring effect dominates the entrenchment effect. In India, corporate sector is dominated by concentrated ownership with the control in the hands of family owners. The main characteristic of business groups is the presence of controlling shareholders. The results indicate that the agency problem is not a big threat for firm performance in presence of ownership opacity for the group-affiliated firms. Although ownership opacity might help them to extract private benefits mainly by expropriating the wealth of the minority shareholders or tunneling, the other advantages of being opaque outweigh the negative impact of opacity. According to the entrenchment hypothesis, as firms become increasingly opaque, the extraction of firm resources by the controlling shareholders will face less and less reprisal by the minority or outside shareholders. As a result, with the increase in opacity, firm performance decreases (La Porta, Lopez-de-Silanes, and Shleifer 2002). On the other hand, the monitoring hypothesis argues that effective monitoring by the controlling shareholders will give them an additional power to increase their monitoring mechanism which usually provides competitive as well as cost advantages to the firms. These advantages generate from the fact that the firms by staying opaque have to incur less amount of expenditure for disclosing information and also by being so, they prevent their rivals from acquiring valuable information about the firms (Anderson et al. 2009). This signifies a positive relationship between opacity and firm performance. Going by these arguments, it is clear from the results that entrenchment may be subdued by propping and effective monitoring by controlling shareholders. Extending the argument of Anderson et al. (2003) with respect to founding families to Indian group firms (typically characterized by family control), we argue that controlling shareholders of the group may be in their own interests will try for long-run survival of the firm. Moreover, group family reputation is also associated with these firms; controlling shareholders will act as committed monitors and try to safeguard not only their own interests but also that of the outside shareholders (Anderson et al. 2009). Hence, entrenchment may be subdued by propping and effective monitoring by controlling shareholders. However, Sarkar et al. (2008) point out that one of the symptoms of agency costs in listed firms is opportunistic ‘earning management’ by which the firms distort the actual financial performance with an objective to gain private benefits at the cost of minority shareholders. Hence, it is also possible that the positive relationship between opacity and firm performance arises due to the manipulation of accounting information, which does not truly reflect the fundamentals of the firms. The motivation of doing so obviously comes from the underlying desire of the controlling

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shareholders to conceal different ways by which they expropriate the minority shareholders for acquiring and retaining private benefits. This phenomenon comes under the entrenchment hypothesis. If this is the case, then entrenchment effect dominates the monitoring effect. On the other hand, if we look at the wedge variable, another group firm characteristic, we find that, it has a negative but insignificant impact on firm performance. However, only at 0.10 quantile, wedge has a negative and significant impact on performance measured by ROA. Hence, the findings do not support the studies of Claessens et al. (2002); La Porta et al. (2002); Barontini and Caprio (2006); Villalonga and Amit (2006). Thus, it cannot be said that controlling shareholders of the family-controlled firms use control-enhancing mechanisms to isolate control rights from cash flow rights for expropriating private benefits (DeAngelo and DeAngelo 1985; Johnson et al. 2000), which usually leads to negative performance of the firms. For group-level characteristics, we find that group diversification does not have any significant impact on firm performance irrespective of whether performance is measured by Tobin’s Q or ROA. This refutes the findings of Kali and Sarkar (2005) and indicates that in the post-reform period, the unrelated diversification by groupaffiliated firms does not help in improving their performances. This refutes the type II agency theory. On the other hand, when firm performance is measured by ROA, the presence of internal capital market has a positive and a significant impact on firm performance at all levels of quantiles. This suggests that even with the development of external market, the group firms still enjoy the benefits of internal market. Hence, it supports the internal capital market theory. But when firm performance is measured by Tobin’s Q, we find the relationship between the presence of internal capital and firm performance to be insignificant for the firms at all the quantiles. Hence, the stock market performance does not depend on internal capital as such. The findings suggest that none of the arguments explained before (in Sect. 8.1) in support of positive or negative relationship between group affiliation and firm performance are perfectly suitable to explain the better performance of the group-affiliated firms as against the stand-alone firms in Indian manufacturing sector. However, considering the positive association between group affiliation and firm performance, it is apparent that the agency problem perhaps does not persist. Further, with the improvement in the institutional environment of the country, financial disclosures of the firm have been somewhat made mandatory and the external financial market has also been developed. This indicates that group-affiliated firms may be transparent enough to acquire external at a lesser cost than that of the stand-alone firms. Hence, from the Resource Dependency Theory perspective, the reduction in uncertainty to obtain external resources has made the affiliated firms better performers than that of the stand-alone firms. However, even with the sea-change in the external environment of Indian economy, our findings show that the ownership opacity is still present in the group-affiliated firms and surprisingly, ownership opacity has a positive influence on firm performance. This indicates that even though agency problem apparently does not exist, it can also happen that if the controlling shareholders distort the financial information, then inspite of having a positive relationship between group affiliation

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and firm performance, agency problem dominates. On the other hand, the profitability of the affiliated firms is still highly affected by the internal capital market. This suggests that in the post reform period, the affiliated firms are taking advantages of both the internal and external capital market. This signifies that findings of our study do not support the institutional void theory and transaction cost theory. Instead, our findings can be explained with the help of the resource-based view and the resource dependency theory. From the resource dependency theory perspective, as the external capital market develops, the affiliated firms try to establish a link with the external actors to acquire resources, which lead to the reduction in uncertainty of getting resources. This in turn helps in improved performance of firms. On the other hand, from the point of resource-based view, the firms at the same time are also dependent on its vast and unique internal resources which can be used for increasing its dynamic capabilities to address the rapidly changing environment. With the increase in their capabilities, the firms are expected to exhibit better performance.

8.6 Conclusion This article has examined whether group-affiliated firms outperform the stand-alone firms in the post-reform period that spans from 2000–01 to 2012–13. Our analysis is based on 14,274 numbers of BSE-listed Indian manufacturing firms, out of which 6565 numbers are group-affiliated firms and 7709 number of stand-alone firms. By applying linear dynamic panel data regression model, we find that the performance of group-affiliated firms far excels the standalone firms. In order to find the factors responsible for better performance of group-affiliated firms as against the standalone firms, we use both dynamic panel data regression technique and panel quantile regression method and find that ownership opacity is one of the factors for better performance of group-affiliated firms irrespective of whether the performance is measured by Tobin’s Q and ROA. However, when ROA is the performance measure, along with opacity, internal financial capital also plays a significant role for improved performance of group-affiliated firms. The findings suggest that with the change in the institutional environment of the economy, agency problem may persist. While institutional void is no longer valid in the post-reform period, the positive association between group affiliation and firm performance can be explained by resource-based view and resource dependency theory.

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Chapter 9

Related Party Transactions and Stock Price Crash Risk: Evidence from India Ekta Selarka and Subhra Choudhury

Abstract Related Party Transactions disclosures in Annual Reports have recently gained more attention of the Indian policymakers. This paper aims at finding out the effect of related party transactions disclosure on the stock price crash risk faced by the firms. Using a large sample of all the NSE listed firms for the period 2005– 2012 this study provides evidence that related party disclosure is associated with a decrease in the stock price crash risk faced by the firms. This finding is consistent with the view that information asymmetry increases crash risk. In addition to this, the study finds that such decrease is observed more in the firms with higher risk.

9.1 Introduction Corporate governance literature has emphasized the role of extent and quality of corporate disclosures in the context of protecting shareholder’s interests. In this context, related party transactions (RPTs) have emerged as one of the recurring areas of concern in both developed as well as developing economies. These transactions are often diverse complex business transactions between a company and its key personnels, directors, or principal owners. As a result, not only they are considered difficult to audit but also abuse of such transactions can be detrimental to minority shareholder’s wealth (Johnstone and Bedard 2004; OECD 2012). This is consistent with the conflict of interest hypothesis (Jensen and Meckling 1976). On the other hand, related party transactions that are carried out at “arm’s length” can reduce transaction costs and further increase the profitability of the company thereby increasing the overall value to the shareholders. This is consistent with efficient contracting or efficient transactions hypothesis (Kohlbeck and Mayhew 2004; Gordon et al. 2004). These conflicting hypotheses suggest that effect of disclosing RPT is an empirical question that captures the tradeoff between a) management’s incentive to report competitive transactions and thereby reduce the agency risk in share price and b) E. Selarka (B) · S. Choudhury Madras School of Economics, Chennai, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_9

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a source of entrenchment by management or insiders and increase the agency risk in share price. In this study, we investigate the relationship between disclosure of RPT and stock price crash risk. Our study aims to contribute to an emerging area of research examining RPTs that has evolved due to the role RPTs have played in a number of audit and accounting failures around the world (Erickson et al. 2000; Gordon et al. 2004; Shastri and Kahle 2003). Theoretical models incorporating incomplete transparency predict that occasional (individual firm) stock price crashes occurs as accumulated negative firm-specific information suddenly becomes publicly available (Jin and Myres 2006). Empirical studies have found a link between information opacity crash risk (Hutton et al. 2009). Managers are motivated to withhold negative information due to a wide range of incentives, such as compensation contracts, career concerns, and empire building (Ball 2009; Kothari et al. 2009). Therefore, stock price crashes are likely to occur among firms with high agency risk as withholding, delaying or accumulating the disclosure of bad news is unsustainable for long periods and will eventually lead to significant stock price crashes when the true fundamentals unexpectedly reveal an enormous amount of negative information in the market (Bleck and Liu 2007; Callen and Fang 2013). Notwithstanding with measures to improve market efficiency and liquidity that accommodates the flow of information in the market, stock market regulators around the world have also focused upon higher information disclosure of publicly available information through regulated laws and highlighting voluntary best practices which can become norms in future course of time. In this context, agency perspective predicts positive effect of disclosure about RPTs in affecting stock price crash risk by reducing the information asymmetry associated with corporate transactions. Studies have shown that firms in developed countries also use RPT as a means to transfer out income and assets for the benefit of those who control them (Johnson et al. 2000). Empirical studies from both developed and developing countries have found significant effects of corporate governance mechanisms on mitigating agency costs. With respect to stock price crash risk, a study by Andreou et al. (2016) shows insiders’ ownership, accounting conservatism, board size and the presence of a corporate governance policy mitigate crash risk. In the context of corporate governance in concentrated ownership structures conflict of interest between minority shareholders and majority shareholders can accentuate as these structures give opportunities of “tunneling” corporate resources. Concentrated ownership and business groups are norms in the emerging and transition countries (Claessens et al. 2002). Business group ownership structures in general have larger scope for RPTs due to access to the internal capital market. These businesses can further use their pyramidal structures to conduct related party transactions to inflate or deflate their profits in order to evade taxation, to manipulate their earnings either upward or downwards, to decrease shareholder return, or simply to maximize the individual benefit of the executive officers. Withholding RPT information increases information asymmetry in the market. This in turn adversely affects the transparency in fundamental the value of the firm and increases the crash risk,

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as elaborated in the previous section. When this type of activity is undertaken by a large number of firms it will have cascading effect on the equity market as a whole. To build our hypotheses that link agency risk with crash risk, we look at the empirical literature along the following dimensions. The first set of studies focuses on (1) the impact of RPTs on firm valuation, (2) association of RPTs with strategic corporate decisions that directly capture agency costs, and (3) agency perspective in explaining the crash risk. RPTs have found to negatively affect the company’s operating performance measured by return on assets of Indian companies. Jian and Wong (2010) find evidence for propping of earnings through related party sales in Chinese SOEs. Cheung et al. (2009) document evidence on tunneling and propping through related party transactions associated with controlling owners. The authors also find that information disclosure is significantly less (more) with RPTs representing tunneling (propping). With respect to the firm valuation associated with RPTs, Kohlbeck and Mayhew (2010) find that firms disclosing RPTs have significantly lower market valuation. Using earnings management as a measure of opacity which is also associated with agency cost, Hutton et al. (2009a, b) find that opaque firms which reveal that less information are more prone to stock price crashes. Further, the market can comprehend information related to extraction of private benefits and react in the form of crash risk. For example, excess perks are positively correlated with crash risk in Chinese SOEs (Nianhang et al. 2014). The authors argue that to enjoy more perks, executives build up their empire by pretending to have valuable investment opportunities, which is, in turn, masked by presenting the firm’s good performance. The aforementioned diversions of firm resources incentivize executives to withhold bad news for extended periods. Bad news hoarding eventually reaches a tipping point and leads to a stock price crash. However, strong external monitoring makes it harder for executives to withhold bad news from investors and, in turn, can mitigate the impact of excess perk consumption on crash risk. Taking the evidence together, we hypothesize that the empirical nature of association between related party transactions and stock price crash risk allows us to investigate the direct link between the agency cost factored in and the price risk. Our study contributes to the existing literature on corporate decisions affecting the future stock price crash risk by focusing on RPTs which are perceived as to contribute to agency risk in share price due to intrinsic opacity and lack of control by shareholders especially in emerging markets with dominance of concentrated ownership structures. Our study adds to understanding of the impact of disclosure effects of RPTs in an emerging market context where despite being a strong institutional framework in place, enforcement of regulation remains as a challenge. India as our country of study is a natural choice where one of the biggest accounting frauds came to light when insiders attempted to indulge into RPTs to cover manipulation of earnings.1 This further led to the mandate on RPT disclosures enacted through Companies Act 1

In 2008 board of Satyam Computers chaired by the promoter Mr. B. Ramalinga Raju put forward a proposal to buy a company Maytas, which was owned by relatives of the Satyam promoter. This deal was further called off due to resistance from the investors. Following the disapproval, on January 7, 2009 Mr. Raju resigned from the chairmanship and confessed about fudging the accounts of

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2013. In addition to the disclosure, these RPTs should be approved by the board of directors. The link between information disclosure and stock price crash risk motivates us to investigate if the stock price crash risk faced by firms can be explained by RPT disclosure keeping all other things constant. Our results show that disclosure of RPTs is associated with reduction in stock price crash risk after controlling for other variables that affect stock price crash risk. Additionally, such effect is only present for firms with higher price risk in general. This paper is organized as follows. The next section presents the institutional framework and laws governing such parties and transactions in India. Section 9.3 describes the data and methodologies that we use to analyze the empirical question. Section 9.4 presents the empirical findings and Sect. 9.5 concludes our study.

9.2 Related Party Transactions in India: The Institutional Context Over the last decades, related party transactions have gained more importance in the Indian economy. There had been several amendments in the related regulations: 1. 2. 3. 4.

The Companies Act, 1956 Indian Accounting Standard 18 Clause 49 of the Listing Agreement Companies Act, 2013.

9.2.1 The Companies Act, 1956 The Companies Act, 1956 has governed Indian companies. Prior to the amendment in 1999, it had provided limits on investment by a company in other corporate bodies, whether in the same group or outside the group (Sections 372 and 370). Similar limits were applied to inter-corporate loans as well as loans that could be advanced to companies in the same group. After a special resolution is passed in the general meeting, central government approval was required for loans exceeding this limit (Ramaiya, 1988). This law was amended and Section 372A was introduced. This provision now applies to include inter-corporate loans deposits, investments, guarantees, and securities in connection with loans to another public body corporate. Any transactions beyond the specified limits need approval by the annual general meeting through a special resolution. This does not apply for the loans given to any individual firm, trust, or mutual fund. It also mentions about penalty if this is violated. Section 299 of the Act requires the disclosure of interest by a director in a the company of over Rs. 7800 crore. Profits, cash flows and income for the firm were inflated. To justify this, the company had to carry additional amount of resources and assets. To fill this gap the decision to buy Maytas was taken.

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board meeting in case the director is interested in any contract that the company is proposing to enter into.

9.2.2 Indian Accounting Standard 18 The Indian Accounting Standard 18 (Ind AS 18) covers the disclosure requirement of RPTs. Detailed definition of related parties under Ind AS18 is given in Box 1 of Appendix. There is no specific format for reporting RPTs under AS18. It gives a provision for aggregating the transactions that are less than 10 percent of the monetary value of the total transactions of the same nature. The requirement of disclosure includes: . . . .

Name of the related parties involved in transactions; Description of the relationship between the involved parties; Description of the nature of transactions between them; Volume of the transactions done either as an amount or as an appropriate proportion . Any other necessary elements of related party transactions or an understanding of the financial statements; and . Amount or appropriate proportions of outstanding items.

9.2.3 Kumar Mangalam Birla Committee Report and Clause 49 In early 1999 a committee was set up under the leadership of Mr. Kumar Mangalam Birla, which focused on promoting and raising the standards of good corporate governance in India. In the year 2000, stock market regulator, Securities and Exchange Board of India (SEBI) accepted the key recommendations of Birla committee and incorporated these into Clause 49 of the Listing Agreement of the Stock Exchanges. Clause 49 requires a company to (voluntarily) disclose materially significant related party transactions that may have potential conflict with the interests of company at large, this may include transactions of material nature, with the promoters, the directors or the management, subsidiaries of the company or relatives etc.

9.2.4 Companies Act, 2013 The Companies Act 2013, brought about some changes in provisions for related party transactions. However, most of the provisions under Section 188 of 2013 Act

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are quite similar to the requirements under Sections 297 and 314 of the 1956 Act. Some of the important changes as in the 2013 Act include the following: . Need for central government approval for loans exceeding the permissible limit was removed. . It widened the list of transactions such as leasing of property of any kind, appointment of any agent for purchase and sale of goods, material, services or property. . Cash at prevailing market price was replaced with ‘arm’s length transaction’. . Related party transactions have to be included in the board’s report along with justification for entering into such contracts and arrangements. Other than these, The Income Tax Act 1961 also contains provisions related to transfer pricing issues on related party transactions. International Accounting Standard, IAS 24, of IFRS was issued at 1st January 2012 which provides the international definition of Related Party transactions and lays down the norms for related party disclosures. It defines a related party transaction as “a transfer of resources, services or obligations between a reporting entity and a related party, regardless of whether a price is charged”. Under IAS24, any entity involving in any related party transactions during periods covered by the financial statements is required to disclose about the nature of the related party relationship. At a minimum level, disclosures shall include the amount of transactions and outstanding balances inclusive of commitments, terms and conditions of the transactions, details of any guarantees received or given, provision of doubtful debts and the expenses with respect to doubtful debts respectively. Disclosures should be done separately for “the parent, entities with joint control or significant influence over the entity, subsidiaries, associates, joint ventures in which the entity is a venture, key management personnel of the entity or its parent and other related parties”. Finally, a peer comparison of countries with regulation of RPT disclosure shows that most of the countries like Belgium, France, Italy, Israel, Brazil, Russia, South Africa follow IFRS for their definition of Related Parties and disclosure norms. China diverges somewhat from the IFRS because of its different ownership structure. China does consider the transactions between state owned enterprises as Related Party Transactions. However, there are some minor differences across the countries. For example, Belgium applies IAS 24 rules on the consolidated accounts. The French legal system makes a distinction between “related party transactions” which are accounted for and reported according to IAS 24 standards within the context of consolidated company group accounts, and a specific approval process called “conventions réglementées” (literally this can be translated as “regulated agreements”). Brazil requires disclosure according to IAS 24 both in the consolidated and individual account. In South Africa, it has been expanded beyond IAS 24 to include related-party transactions with jointly controlled entities, and to include related-party transactions where both parties are controlled by the state. Other countries like Chile and Korea does not follow IAS 24. Chile’s Companies Law states that a listed company can only undertake a Related Party Transaction (RPT) if the transaction complements the company’s social interest, is conducted according to market practices, and is

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disclosed to and approved by the majority of the board. Most of the countries have a threshold limit. Any related party transaction above that limit is considered to be material and it must be disclosed. At present, Indian Accounting Standards does not follow IFRS. However, with the Ind IAS 24, India is also trying to converge with the international norms.

9.3 Data, Hypotheses and Methodology We draw our basic samples from 1757 firms listed on National Stock Exchange (NSE) between 2005 and 2012 from Prowess database maintained by the Center for Monitoring Indian Economy. Selection of 2005 as the first period of study is motivated by the fact that by this time corporate governance regulations were extended to all listed firms. Similarly, selection of 2012 as end period in our study is chosen as new Companies Act was enacted in 2013 followed by which there is a sharp increase in number of firms reporting RPTs. As voluntary disclosure of RPT is crucial to our study we stop at year 2012. Further, we exclude financial companies and observations information on ownership structure, stock prices and financial variables are not available. Our final sample includes 1478 companies over period of 2005–2012. Data on RPT is available for different types of related parties i.e. Subsidiaries, holding company, parties where control exists, Key personnel and their relatives, and others respectively. Under each type of related party the transactions are available across capital account payments and receipts, and total revenue income and expenditure. Table 9.1 shows the distribution of firms disclosing RPTs across our sample firms. It is evident that majority of firms engage into RPTs. The testable hypotheses are defined as follows: H1: Related Party Disclosures Decrease the Crash Risk Faced by the Companies

This prediction of negative relation is based on the fact that disclosure of related party transactions decreases the information asymmetry in the market, which is one Table 9.1 Distribution of firms disclosing RPT over sample period

Fiscal year

No. of firms

Firms disclosing RPT (%)

2005

1201

1044 (0.87)

2006

1296

1161(0.89)

2007

1336

1239(0.93)

2008

1365

1285(0.94)

2009

1406

1297(0.92)

2010

1439

1334(0.93)

2011

1460

1369(0.94)

2012

1450

1374(0.95)

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of the factor responsible for elevating the crash risk faced by a company and hence it decreases the crash risk faced by the company. H2: Related Party Disclosures Decrease the Crash Risk for the Companies with Higher Crash Risk

The effect of RPT disclosure on risk may not be the same for all levels of risk. Acceptance of this hypothesis implies that companies with higher risk can decrease their risk by disclosing the related party transactions. Companies with low crash risk have low information asymmetry and high investor confidence. For such companies disclosure may not have any effect. However, for companies with high crash risk have high information asymmetry in general, disclosure of RPT reduces information asymmetry and decreases risk. We use two measures of crash risk—negative conditional skewness (NCSKEW) and down-to-up volatility (DUVOL) respectively computed from firm-specific daily returns. Firm specific daily returns are estimated using the natural log of one plus residual returns, denoted by W from the following extended market model: r j,t = α + β1, j rm,t−2 + β2, j rm,t−1 + β3, j rm,t + β4, j rm,t+1 + β4, j rm,t+2 + εi,t where rj,t is stock j’s daily return on trading day t, and rm,t is daily market return (NIFTY index) on trading day t. Two days of lag and lead are added to account for the effect of non-synchronous trading. The Negative Conditional Return Skewness (NCSKEW): NCSKEW for a given firm in a fiscal year is calculated by taking the negative of the third moment of firmspecific daily returns for each sample year and dividing it by the standard deviation of firm-specific daily returns raised to the third power (Chen et. al. 2001). Specifically, for each firm j in year t, we compute NCSKEW as [

N C S K E W j,t

] W1t3 = −[ (E 2 ) 23 ] W1t (n − 1)(n − 2) 3

n(n − 1) 2

E

Here, n is the number of firm-specific return observations during year t. The Down-to-up Volatility (DUVOL): For any stock jin year t we separate all the days with returns below the period mean (“down” days) from those with returns above the period mean (“up” days), and compute the standard deviation for each of these subsamples separately. We then take the log of the ratio of (the sample analog to) the standard deviation on the down days to (the sample analog to) the standard deviation on the up days. Thus we have

DU V O L j,t

]⎫ ⎧[ E ⎨ (n U − 1) D O W N R 2j,t ⎬ ] [ = log ⎩ (n − 1) E R 2 ⎭ d UP j,t

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where Rjt represents the sequence of de-meaned daily returns to stock j during period t; n U and nd are number of days when the price moved up and down respectively. In both the cases a higher value indicates a greater crash risk. Finally, we estimate the following equation: crash_riskit+1 = β0 + β1 R P Tt + βk X kit + εit

(9.1)

where crash_risk is measured in terms of NSKEW and DUVOL, RPT is a dummy variable that takes a value of 1 if the company has reported RPT under any category, zero otherwise. Vector X is a set of firm-specific control variables. Specifically control variables include standard deviation of weekly returns (SIGMA), average weekly returns (RET), log of market capitalization (SIZE), long term debt to total assets (LEV), return on asset (ROA), promoter shareholding (PROM) and market to book value ratio (MBVR). We also include group dummy that equals one if the firm belongs to business group and zero otherwise. Finally, all the regression specifications include industry dummy variables constructed from two-digit National Industrial Classification (NIC) to account for industry specific business cycles and year dummies to account for time effects. For robustness, we also estimate a logistic regression to see how the amount of RPT disclosed affects the probability of facing a crash risk as: log(odds_crash_riskit+1 ) = β0 + β1 log(R P Tt ) + βk Xkit + εit For H2 we run quantile regressions for the Eq. (9.1) at different quantiles.

9.4 Empirical Results Figure 9.1 shows crash price risk of all the NSE listed firms across years and Fig. 9.2 shows the same according to the ownership categories. In 2008 crash risk faced by the firms increased. From Fig. 9.2 it can be seen that the foreign firms listed in NSE were more affected by the crisis. Table 9.2 presents the descriptive statistic for all the variables. The mean value for NCSKEW is −0.48 and for DUVOL is −0.32. This suggests that the sample studied Fig. 9.1 Crash risk over years

CRASH RISK

NCSKEWT

0.2 0 -0.2 -0.4 -0.6 -0.8 -1

2005

2006

2007

2008

2009

2010

2011

2012

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Fig. 9.2 Crash risk over years for different ownership structures

CRASH RISK ACROSS OWNERSHIP STRUCTURES 0.2 0 -0.2

2005

2006

2007

2008

2009

2010

2011

2012

-0.4 -0.6

-0.8 -1 -1.2 -1.4

Indian Firms Foreign Firms Indian Govt. And Cooperative Firms

is not crash prone on an average and our analysis is not drawn on firms facing crash risk in general. On an average 85% of our sample firms report at least one RPT. Initial observation shows that transactions by RP except key personnels and relative account for 51% of the RPT disclosures where type of RP is a subsidiary. Second major category of RPT is where RP is “key personnels and relatives” which accounts for 36% of RPTs. With respect to the type of RPT, RP expenditures account for 34% of RPTs, RP sales accounting for 15%, RP current receivables accounting for 18% and RP loans accounting for 10% respectively. Table 9.3 shows the correlation coefficients for all variables. Both the measures of risk, NCSKEW and DUVOL are highly correlated, with a correlation coefficient of 0.86. RPT is negatively related to both the crash risks. H1 predicts that RPT disclosure is negatively related to future stock price crash risk because it reduces information asymmetry in the market. Tables 9.4, 9.5 and 9.6 Table 9.2 Descriptive statistics for all variables Variables

Mean

S.D

5 percent

25 percent

Median

75 percent

95 percent

Risk Measures NCSKEW

−0.478

1.025

−1.746

−0.940

−0.459

-0.074

0.594

DUVOL

−0.324

0.427

−0.939

−0.588

−0.331

-0.084

0.295

RPT

0.85

0.35

0

1

1

1

1

0.005

−0.007

−0.002

0.000

0.002

0.005

Control Variables RET

0.000

SIGMA

0.035

0.012

0.019

0.028

0.034

0.041

0.053

ROA

0.910

0.898

0.062

0.384

0.790

1.228

2.188

LEV

0.430

1.690

0.010

0.144

0.315

0.474

0.794

SIZE

7.789

4.598

6.283

7.610

9.195

11.556

PROM

51.78

17.87

2.134

20.25

40.34

52.59

64.8

78.16

MBVR

2.252

15.88

0.118

0.665

1.304

2.627

7.346

0.0512

−0.0324

−0.0035

0.0804

−0.0368

−0.0024

SIZE

PROM

MBVR

−0.0213

0.02

−0.0341

0.0259

ROA

LEV

−0.0362

−0.0774

SIGMA

−0.0137

0.1401

−0.0075

0.1743

RPT

RET

1

1

0.8553

DUVOL

NCSKEW

NCSKEW

DUVOL

Table 9.3 Correlation coefficients

0.1151 0.0357

0.0033

0.0375 −0.0423

−0.079

−0.4935

−0.1251

0.2499

0.0742

0.0665 −0.0145

−0.0316

1

SIGMA

0.0327

−0.0042

1

RET

−0.0339

−0.1677

0.009

1

RPT

0.0285

0.1185

−0.0791

−0.06

1

ROA

−0.0134

−0.07

−0.1173

1

LEV

0.1041

0.1571

1

SIZE

0.0365

1

PROM

1

MBVR

9 Related Party Transactions and Stock Price Crash Risk: Evidence … 243

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present the multivariate regression analyses for testing H1, with the full set of control variables. In each of these tables Model 1 uses NCSKEW as a risk measure, model 2 uses DUVOL and model 3 uses a cross measure of both NCSKEW and DUVOL. Model 3 considers a firm to be risky if and only if it is risky by both the measures. Tables 9.4 and 9.5 use the pooled regression method with industry and year dummies. To alleviate concern about potential cross-sectional dependence in the data, we report z-values using robust standard errors corrected for industry clustering. Table 9.4 reports that the coefficient of RPT is −0.084 and −0.034 respectively. This implies that on average, with other things remaining constant, for firms disclosing RPT crash risk is lower than those not disclosing RPT by 0.084 (for NCSKEW) and 0.034 (DUVOL). Table 9.4 Effects of RPT disclosure on stock price crash risk (pooled)

NCSKEWT+1

DUVOLT+1

−0.084***

−0.034**

(−3.810)

(−2.350)

40.424***

21.641***

(8.490)

(−3.81)

RPT Measures RPTT Control Variables RETT SIGMAT ROAT LEVT SIZET PROMT MBVRT Intercept

3.070***

1.397***

(3.010)

(−3.27)

−0.005

−0.005

(−0.200)

(−1.070)

0.058***

0.029**

(2.850)

(−2.22)

0.044***

0.023***

(12.670)

−17.57

−0.002***

−0.001***

(−3.910)

(−4.310)

−0.001

0

(−1.150)

(−1.260)

−1.093***

−0.665***

(−16.740)

(−28.020)

Group dummy

Yes

YES

Industry dummy

Yes

YES

Year dummy

Yes

YES

R2

0.097

0.19

Note Here *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Here a pooled OLS model has been used

9 Related Party Transactions and Stock Price Crash Risk: Evidence …

245

Table 9.5 Effects of RPT disclosure on stock price crash risk (pooled logit) NCSKEWT+1

DUVOLT+1

BOTH NCSKEWT and DUVOLT

−0.033*

−0.045***

−0.047***

(−1.870)

(−4.820)

(−5.700)

65.394***

53.798***

69.252***

(13.960)

(−6.7)

(−14.16)

SIGMAT

5.114*

5.371*

4.142

(1.670)

(−1.72)

(−1.28)

ROAT

−0.133***

−0.056*

−0.125***

(−6.420)

(−1.630)

(−4.090)

0.170***

0.069

0.084*

(2.960)

(−1.27)

(−1.79)

SIZET

0.152***

0.132***

0.156***

(20.200)

(−10.21)

(−13.1)

PROMT

−0.004***

−0.005***

−0.005***

(−3.660)

(−4.020)

(−4.190)

0.000

0

0

(0.000)

(−0.150)

(−0.250)

Intercept

−3.463***

−3.598***

−3.893***

(−18.020)

(−14.780)

(−14.280)

Group dummy

Yes

Yes

Yes

Industry dummy

Yes

Yes

Yes

Year dummy

Yes

Yes

Yes

Pseudo-R2

0.097

0.118

0.109

Marginal effect of RPT t-1

−0.0048*

−0.0057***

−0.0051***

(at means)

(−1.83)

(−4.61)

(−5.15)

RPT Measures RPTT Control Variables RETT

LEVT

MBVRT

Note Here *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively

Finally, Table 9.6 presents the results of the effects of RPT on stock price crash risk (Logit model in a panel data frame work). Tables 9.5 and 9.6 test the primary hypotheses using logistic regression. Table 9.5 uses a pooled regression where the coefficients of RPTt are −0.033, −0.045 and −0.047 for models 1, 2 and 3 respectively. This implies that disclosure of RPT is negatively related to stock price crash risk. In the above regression setup we included year dummy and industry dummy variables to control for year and industry heterogeneity. However individual firm heterogeneity was not captured in the above model. So next in Table 9.6, we used the same regression in a panel data frame work. Under this setup also the results were

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Table 9.6 Effects of RPT on stock price crash risk (panel logit) NCSKEWT+1

DUVOLT+1

BOTH NCSKEWT+1 and DUVOLT+1

−0.036**

−0.051***

−0.052***

(0.016)

(0.017)

(0.018)

86.574***

82.011***

91.045***

(7.784)

(8.066)

(8.554)

−16.956***

−22.137***

−19.020***

(3.246)

(3.479)

(3.684)

−0.133**

−0.077

−0.133**

(0.053)

(0.053)

(0.058)

0.211***

0.095*

0.101**

(0.069)

(0.049)

(0.049)

0.141***

0.119***

0.146***

(0.018)

(0.019)

(0.020)

−0.006***

−0.007***

−0.007***

(0.002)

(0.002)

(0.002)

0.000

0.000

0.000

(0.002)

(0.002)

(0.002)

−1.569***

−1.341***

−1.823***

(0.239)

(0.246)

(0.260)

Group dummy

Yes

Yes

Yes

Industry dummy

Yes

Yes

Yes

RPT Measures RPTT Control Variables RETT SIGMAT ROAT LEVT SIZET PROMT MBVRT Intercept

Note Here *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively

similar. Here the coefficients of RPTt-1 are −0.036, −0.051 and −0.052 respectively. This implies that disclosure of RPT is negatively related to stock price crash risk. The marginal effect of RPTt-1 on NCSKEW, DUVOL and Both NCSKEW and DUVOL are −3.59%, −5.12% and −5.2% respectively. All the Marginal effects are significant. This implies that for every percentage increase in the amount of RPT disclosed the probability of a firm facing a stock price crash decreases by the above percentages. Given that on an average 20.9% (by NCSKEW measure) and 18.4% (by DUVOL measure) of listed firms in India face crash risk. These findings provide suggestive evidence that an association between crash risk and RPT disclosure is important for the economy as a whole. The coefficients of the control variables are generally consistent with the findings of prior studies. PROMt is negatively related to crash risk. This is consistent with the efficient monitoring hypothesis which implies that higher control rights with

9 Related Party Transactions and Stock Price Crash Risk: Evidence …

247

controlling shareholders reduces the crash risk due to their incentives to monitor the management. SIGMAt , RETt , SIZEt , LEVt have positive impact on the crash risk and ROAt is negatively related. MBVRt is insignificant in all the cases. H2 predicts that RPT disclosure reduces stock price crash risk for the high risk companies. Effect of RPT disclosure may not have the same effect for all the firms. Companies where crash risk is very high indicates that information asymmetry is very high which implies that for such companies RPT disclosure reduces the information asymmetry in the market and hence reduces stock price crash risk. On the other hand, companies with lower crash risk have lower information asymmetry and therefore have higher investors’ confidence. For such companies disclosure of RPT may not have any significant effect. Table 9.7 presents the multivariate regression analyses for testing H2, with the full set of control variables. We use a quantile regression for this purpose. We estimate the relationship between RPT disclosure and crash risk at 5 percent, 10 percent, 25 percent, 50 percent, 75 percent, 90 percent and 95 percent quantiles of crash risk respectively. Industry and year dummies have been included to account for year and industry heterogeneity which may contribute to the crash risk of the stock irrespective of disclosure practices. RPT measure is a dummy variable which takes the value 1 if the company discloses RPT else it is 0. To assign firms in crash risk quantiles, DUVOL has been used as a measure of stock price crash risk. Regression coefficient for RPT variable was significant for 50% (−0.025), 75% (−0.045), 90% (−0.048) and 95% (−0.074) quantiles respectively. It is insignificant for the quantiles below 50%. This shows that PRT disclosure does not have the same effect on crash risk for all levels of risk. RPT disclosure reduces crash risk for the companies with very high crash risk. Also, it can be noted that the absolute value of the coefficient increases from 50 percent quantile to 95 percent quantile. This implies that the impact of RPT disclosure on crash increases with the risk level of the company.

9.5 Conclusion This study investigates the effect of related party disclosure on the stock price crash risk using a sample of Indian firms during a period 2005–2012. Given the concentrated ownership structure which leads to higher information asymmetry our study contributes to the literature by examining the role of information disclosure of corporate transactions. Our findings show that related party disclosure decreases by the crash risk faced by the companies. The results obtained are robust to the use of different crash risk measures. The results are also robust to the different models and approaches used for the study. Overall our findings are consistent with the asymmetric information aspect of RPT disclosure. RPT disclosure reduces the information asymmetry in the market about a stock and thus reduces its crash risk. Our analysis also shows that RPT disclosure reduces the crash risk for the companies with very high crash risk and has no significant effect fir the companies with low risk. The effect is greater for the higher risk companies.

MBVRT

PROMT

SIZET

LEVT

ROAT

SIGMAT

RETT

Control Variables

RPTT

RPT Measures

(1.420)

(1.710)

(−1.300)

(−1.760)

0.000

−0.001

−0.001*

0.000*

0.018***

(3.910)

0.016***

(2.540)

(8.550)

(9.040)

(-0.530)

(-0.610)

0.071***

−0.006

−0.009

0.096***

1.368

(1.490)

−0.691

(−0.480)

15.893***

(5.100)

20.159***

(3.580)

−0.048**

(−2.400)

−0.074***

90 Quantile

(−2.860)

95 Quantile

(0.010)

0.000

(−3.100)

−0.001***

(7.560)

0.024***

(6.170)

0.043***

(-0.640)

−0.005

(3.570)

2.105***

(7.890)

13.273***

(−3.060)

−0.045***

75 Quantile

Table 9.7 Effects of RPT on stock price crash risk (Quantile regression)

(−1.100)

0.000

(−4.710)

−0.001***

(11.460)

0.028***

(2.180)

0.013**

(-1.150)

−0.008

(4.470)

2.115***

(11.070)

13.637***

(−1.990)

−0.025**

50 Quantile

(−2.100)

0.000**

(−4.290)

−0.001***

(13.390)

0.029***

(2.950)

0.020***

(-0.590)

−0.004

(3.320)

1.501***

(11.410)

11.892***

(−1.340)

−0.016

25 Quantile

(−3.110)

0.000***

(−3.620)

−0.001***

(9.990)

0.030***

(3.650)

0.021***

(0.150)

0.001

(2.990)

2.038***

(7.740)

10.772***

(−1.230)

−0.021

10 Quantile

(continued)

(−2.260)

−0.001**

(−2.880)

−0.001***

(4.510)

0.018***

(3.600)

0.028***

(-0.500)

−0.006

(2.720)

2.132***

(2.680)

5.694***

(0.360)

0.009

5 Quantile

248 E. Selarka and S. Choudhury

0.080

Pseudo-R2

Yes

0.089

Yes 0.111

Yes

Yes

Yes

(−12.520)

−0.539***

75 Quantile

0.127

Yes

Yes

Yes

(−19.890)

−0.719***

50 Quantile

0.129

Yes

Yes

Yes

(−25.000)

−0.889***

25 Quantile

Note Here *, **, and *** indicate statistical significance at the 10 percent, 5 percent, and 1 percent levels, respectively

Yes

Yes

Industry dummy

Year dummy

(−5.110)

Yes

(−0.360)

−0.321***

Yes

90 Quantile

95 Quantile

−0.032

Group dummy

Intercept

Table 9.7 (continued)

0.119

Yes

Yes

Yes

(−20.300)

−1.048***

10 Quantile

0.111

Yes

Yes

Yes

(−16.380)

−1.073***

5 Quantile

9 Related Party Transactions and Stock Price Crash Risk: Evidence … 249

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The findings of our study can be used to justify the current regulatory requirements in Indian corporate sector that leads to reduce the overall crash risk of the stock market of the economy by emphasizing on mandatory disclosure of related party transactions and by imposing heavy penalty in case the companies do not abide by the disclosure norms. As the sample period used for the study was before the implementation of the Companies Act, 2013, which has given greater importance on mandatory disclosure of related party transactions, our findings provide a pre-Act status of effect of mandatory disclosures of RPT on the crash risk.

Appendix Box 1: Related Parties Under the Indian AS18 ndian AS 18 defines related parties as including: (a) enterprises that directly, or indirectly through one or more intermediaries, control, or are controlled by, or are under common control with, the reporting enterprise (this includes holding companies, subsidiaries and fellow subsidiaries); (b) associates and joint ventures of the reporting enterprise and the investing party or venturer in respect of which the reporting enterprise is an associate or a joint venture; (c) individuals owning, directly or indirectly, an interest in the voting power of the reporting enterprise that gives them control or significant influence over the enterprise, and relatives of any such individual; (d) key management personnel and relatives of such personnel; and (e) enterprises over which any person described in (c) or (d) is able to exercise significant influence. This includes enterprises owned by directors or major shareholders of the reporting enterprise and enterprises that have a member of key management in common with the reporting enterprise. Indian AS 18 explicitly excludes the following parties from related party status: (a) two companies simply because they have a director in common, notwithstanding paragraph 3(d) or (e) above (unless the director is able to affect the policies of both companies in their mutual dealings); (b) a single customer, supplier, franchiser, distributor, or general agent with whom an enterprise transacts a significant volume of business merely by virtue of the resulting economic dependence; and

9 Related Party Transactions and Stock Price Crash Risk: Evidence …

251

(c) the parties listed below, in the course of their normal dealings with an enterprise by virtue only of those dealings (although they may circumscribe the freedom of action of the enterprise or participate in its decision-making process): (i) (ii) (iii) (iv)

providers of finance; trade unions; public utilities; government departments and government agencies including government sponsored bodies.

Box 2: Related Parties Under the Ind As24 Related party is a person or entity that is related to the entity that is preparing its financial statements (in this standard referred to as the ‘reporting entity’). (a) A person or a close member of that person’s family is related to a reporting entity if that person: (i) has control or joint control over the reporting entity; (ii) has significant influence over the reporting entity; or (iii) is a member of the key management personnel of the reporting entity or of a parent of the reporting entity. (b) An entity is related to a reporting entity if any of the following conditions applies: (i) The entity and the reporting entity are members of the same group (which means that each parent, subsidiary and fellow subsidiary is related to the others). (ii) One entity is an associate or joint venture of the other entity (or an associate or joint venture of a member of a group of which the other entity is a member). (iii) Both entities are joint ventures of the same third party. (iv) (iv)One entity is a joint venture of a third entity and the other entity is an associate of the third entity. (v) The entity is a post-employment benefit plan for the benefit of employees of either the reporting entity or an entity related to the reporting entity. If the reporting entity is itself such a plan, the sponsoring employers are also related to the reporting entity. (vi) The entity is controlled or jointly controlled by a person identified in (a).

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(vii) A person identified in (a)(i) has significant influence over the entity or is a member of the key management personnel of the entity (or of a parent of the entity).

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Kohlbeck MJ, Mayhew BW (2004) Agency costs, contracting, and related party transactions. Contracting, and related party transactions (December 31, 2004) Kohlbeck M, Mayhew B (2010) Valuation of firms that disclose related party transactions. J Account Public Policy 29(2):115–137 Kothari SP, Shu S, Wysocki PD (2009) Do managers withhold bad news? J Account Res 47:241–276 Morck R, Yeung B (2004) Special issues relating to corporate governance and family control. World Bank Policy Research Working Paper 3406 National Treasury, Republic of South Africa: Accounting Manual for Departments. Related Party Disclosures Nianhang X, Xiaorong L, Qingbo Y, Chan K (2014) Excess perks and stock price crash risk: evidence from China. J Corp Finan 25:419–434 Roe M (1994) Strong managers, weak owners: the political roots of American corporate finance. Princeton University Press, Princeton Related Party Transactions and Minority Shareholder Rights, OECD, (2012) Ricardo Escobar, Partner, Carey y Cia, Chile, (2001), Corporate Governance in Chile: New Developments, OECD Sarkar J (2013) Ownership and corporate governance in Indian firms, Corporate governance: an emerging scenario, national stock exchange (eds) Chapter 9 Shastri K, Kahle KM (2003) Executive loans. Available at SSRN:423447 Srinivasan P (2013) An analysis of related-party transactions in India. NSE Working Paper Series

Chapter 10

Minsky’s Financial Instability Hypothesis: A Theoretical Engagement in the Indian Context Rohit Azad

Stability leads to instability. Hyman Minsky

Abstract This chapter looks at a macro picture of the corporate investment and the role of finance from the lens of Hyman Minsky. India experienced its best ever growth performance during the 2000s but it also ended up with highly leveraged large corporate firms. These firms essentially financed their investment through the commercial banks. As a result, the high growth phase ended with a banking sector stressed by non-performing assets. On the face of it, this looks like what Minsky had said about the booms ending with a financially fragile system but can the Indian case fit that description? Serious macro-theoretical objections have been raised about Minsky’s financial instability hypothesis because it conflates the micro with the macro. While this criticism is valid, I argue that if investment is concentrated in the hands of a few business houses and the credit side of it in a few large banks, a leverage crisis at a micro level can have systemic issues, which is what seems to have happened in the case of India. It is in exploring the role of this concentration, both on the lenders and the borrowers’ side, that this chapter fits the overarching theme of this volume—to explore the role of concentration in business, corporate governance and their relationship with the political class in India.

R. Azad (B) Jawaharlal Nehru University, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 A. Chakraborty and I. Chakraborty (eds.), Indian Business Groups and other Corporations, India Studies in Business and Economics, https://doi.org/10.1007/978-981-99-5041-6_10

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10.1 Introduction The Indian corporate and the banking sectors have been under severe financial stress with the non-performing assets (NPAs) swelling for the public and the private sector banks alike although the trend started with the former, which has of late caught on with the latter as well. It is a matter of concern because it represents the financial health of an economy even as it dries the liquidity up in the economy since banks become wary of extending loans even to reasonable project which under normal circumstances would have qualified for credit by the same lending agencies. Such a squeeze on liquidity thwarts investment. It is, therefore, a matter of great concern to understand why this has happened and Minsky’s financial instability hypothesis comes in handy for that since his work was focused on precisely this aspect of capitalism. He had argued that corporate finance has an inbuilt tendency to generate upswings followed by downswings in the economy. To break out of this endogeneity, policy is required to create fetters to the upswings riding high on a precariously ever-aged corporate sector. The purpose of this chapter is to look at Minsky’s work in the context of the Indian corporate sector. In light of that, the following statement summarizing the effects of the Financial Instability Hypothesis (FIH) of (Minsky 1975, p. 110) makes him amenable to a rigorous empirical enquiry: [D]uring a boom the ratio of debt-financing to investment increases: this is borne out by the available data on corporate debt...

But before I go into the Indian corporate sector, let’s see what the theoretical framework was through which Minsky arrived at this conclusion. Minsky had argued that investment of a firm is determined by the demand and supply price of capital. The former is a price resulting from expected yields per unit of investment discounted by a rate of interest commensurate with the lifetime of the project. So, if a project has an expected life time of 10 years, the relevant rate of discount would be a 10-year bond rate of interest. Since a firm doesn’t have access to infinite finance beyond its own capital, it has to start borrowing from lending agencies. But once it starts doing that, a borrower’s risk kicks in which is not something written on loan contracts but rather something which weighs heavily on the minds of the capitalists. Since interest payments have a primary claim over ex post profits of a firm, a threat of failure of an enterprise would mean not just a loss of own capital but also a heavy loan burden. As the ratio of debt to own fund rises, the borrower’s risk rises further to cover for this margin of safety. As a result of rising borrower’s risk, the net demand price of investment, which is the difference between the demand price and borrower’s risk, falls as investment rises (see the upper arm in Fig. 10.1). Supply price is that at which the project can be newly built. Yet again because of access to finite internal funds, capitalists have to turn to debt finance to fund constructing their projects. Unlike the notional borrower’s risk, however, here there is a risk premium that the lenders write into the loan contracts as the leverage rises to cover their bases against failure of the proposed projects. So, the total supply price of investment, which is

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Fig. 10.1 Minsky’s scissor diagram Source: Fig. 5.4 from Minsky (1975)

the sum of the supply price and lender’s risk, rises with leverage of a firm (see the lower arm in Fig. 10.1). The demand price and the supply price between them determine the level of investment for a firm. Lower the risk premium, higher would be the investment. Minsky argued further that a stable macroeconomic environment gives rise to conditions that generate confidence and, hence, lowering of guards both by the capitalists and the rentiers. In other words, both the borrower’s and the lender’s risk declines during a tranquil economic state. This lowering of the risk premium increases investment, thereby, further fueling an already buoyant economic condition. But this very process means higher leverage for the financial system. Over the course of the boom, firms that were hedged (profits higher than both interest and principal debt commitments) move to a speculative condition (profits covering just the interest part of the debt) and eventually to a ponzi state (where neither interest nor the principal part is covered by profits). A key component of his theory is what determines the point (let’s call it a kink) where the two curves start rising (falling) for the supply (demand) price because if that point itself is dependent on the level of investment, then it is a classic case of chickenand-egg of whether investment determines credit or credit determines investment. But what determines the kink? It is given by that point where the expected internal funds are exhausted for a given supply price. But how can these funds be assumed to be constant since investment generates profits, and, hence, internal funds. If higher investment leads to shifting of the kinks to the right, how can the level of investment be determined by the kink itself? This is by far the most scathing critique of Minsky’s FIH (Lavoie and Seccareccia 2001).

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Business Cycle

Corporate leverage

Fig. 10.2 Corporate leverage during a business cycle a la Minsky Source: Author’s illustration

One way in which Minsky can be defended could be that the investment of one industry doesn’t necessarily get realized as profits in the same industry, in which case the kinks may be independent of the level of investment in a particular industry. But even if this was true, this can surely not hold for the economy as a whole. For all the industries put together, the investments will show up as profits somewhere or the other, so, even if a subset of industries may have a rising leverage (whose investment has not got converted into profits within), the rest of the industries will ipso facto compensate for such a rise, thereby, leaving the average leverage of the corporate sector as a whole the same. So, the statement above is circumspect and has indeed been tested for different countries and the evidence has been found wanting in most cases. Was Minsky then wrong in concluding that corporate leverage is cyclical in nature? I would like to test Minsky’s predicted cyclicality of leverage for the Indian corporate sector for the period 2000–2015 in the next section followed by taking a relook, if required, at Minsky’s FIH in the section following that.

10.2 Stylized Facts for the Indian Corporate Sector on FIH To test the hypothesis of Minsky (1981, 1983, 2016), I take a look at financial fragility (defined as inverse interest coverage ratio) and the debt-capital ratio as two widely accepted markers of financial fragility of the sector (Fig. 10.3). Financial fragility is measured here as the ratio between interest owed to profits earned of the sector

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as a whole. Higher the ratio the more fragile the sector is because it shows that the companies (as a whole) are not even able to cover the interest owed to the lenders. The average ratios presented here are for the entire corporate sector (as covered in the Prowess database). By taking these two ratios, we are able to cover both the flow (interest and profits) and stock (outstanding debt and equity) measures of the corporate sector into account. Does the corporate sector (as a whole) get more leveraged as the economy booms? The second chart in the figure shows that it’s the opposite, i.e. as the economy booms, the debt-equity ratio of the corporate sector as a whole falls.1 The correlation coefficient with respect to GDP growth for both financial fragility and leverage is strongly negative, quite the opposite of what Minsky predicted. This result should not be surprising because this is the macroeconomic fallacy in Minsky’s argument. While it may be true that leverage is rising for certain corporations during the boom, it cannot by definition rise for the corporate sector as a whole because both the numerator and denominator of the leverage ratio rises at the macroeconomic level. Looking at Fig. 10.3, one could easily say that the picture couldn’t have been more conclusive against Minsky’s FIH. Financial fragility and business cycle move in the opposite direction so, a booming economy goes with a less fragile economy and vice versa. The answer is simple – while the interest owed by the corporate sector rises during a boom but so does the profit. It is only when the boom comes to an end for reasons which may have little to do with finance that the profits start dwindling while the interest payment commitments from the past remain unchanged that the system becomes more fragile. Negative correlation between fragility or leverage and economic activity tells us only this much and not about causality but it is possible to delve deeper by looking at the leverage figures at a more disaggregated level. Perhaps the macroeconomic picture is camouflaging what could be happening behind the curtains. For e.g., declining leverage at an average does not mean that this would hold true across different business sectors. If the average picture is also the picture across sectors, then such a system does not necessarily pose a serious financial problem. But what happens if certain sectors that have a high total debt have increasing leverage even as the average leverage falls for the corporate sector as a whole. In what follows, I take the top five industries (at two-digit level) of the Indian economy in terms of their total debt. Those industries (their total debt) are electricity, gas, steam and air conditioning supply (18.8); manufacture of basic metals (10.3), manufacture of coke and refined petroleum products (7.9); telecommunications (6.2); manufacture of chemicals and chemical products (5.7). Between them, they constitute almost half (48.9%) the total debt. Let’s look at the leverage structure of these industries. Is their individual leverage trajectory the same as that of the economy or they divergent? In Fig. 10.4, we can see while three out of these five industries follow the same pattern as the overall average whereas two follow a different trajectory. This has 1

Since 2008 happens to be an outlier in terms of GDP growth rate, it has not been shown in the figure.

260 Fig. 10.3 Whatever happened to Minsky’s FIH Source: Author’s calculation based on the RBI (for the GDP growth rate) and the Prowess database (for the financial ratios)

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Annual Growth Rate of GDP and Financial Fragility of the Private Corporate Sector 0.6

12.0

0.5

10.0

0.4

8.0

0.3

6.0

0.2

4.0

0.1

correlation= -0.60

0.0

2.0 0.0

Financial Fragility (inverse ICR )

GDP(on RHS)

Annual Growth Rate of GDP and Average DebtEquity Ratio of Private Corporate Sector 12.0

2.0 1.8

10.0

1.6 1.4

8.0

1.2 6.0

1.0 0.8

4.0

0.6 0.4

2.0

correlation= -0.27

0.2 0.0

0.0

D/E

GDP (on RHS)

a significant implication. If the patterns of leverage had been the same across the high debt industries, then one could perhaps say that leverage just follows the overall macroeconomic story and, hence, the relationship between the two is mere correlation with not necessarily a causality one and definitely not the one that Minsky was talking about. But divergent patterns of leverage show that even if the economy is booming some industries are getting more leveraged instead of getting deleveraged since their profits (and value of equity) are not rising (may even be declining) as fast as their debt commitments. Even if on the surface things may look unMinskyan, deep down the Minskyan process is on during the second half of this period. In a typical way, this shows that the parts are not merely a fraction of the whole. Even if the macroeconomic picture may

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Fig. 10.4 Different patterns of leveraging across industries

not be alarming, the micropicture is alarming enough, particularly so if the diverging industries constitute a large part of the total debt. And of the two, the power sector happens to have the highest total debt. What implication could this have? Such rising leverage in a few industries could create a contagion effect for the lending institutions and hence just looking at the macroeconomic picture could be misleading. This happens to be the case if we look at the sectoral breakup of stressed advances across the scheduled commercial banks (SCBs). RBI divides the SCBs into three categories: public sector, private sector, and foreign banks. These two divergent industries show on the top when it comes to their share in stressed advances. Their share in stressed advances is almost double their share in total advances for the SCBs as whole but a more disaggregated picture reveals something more.

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Table 10.1 Sectoral breakup of stressed advances Sub-sector

Share in

PSBs

Infrastructure (of which)

Advances

17.6

Stressed advances

30.9

Advances

10.1

Stressed advances

Power generation Telecom

Private banks

Foreign banks

All SCBs

8.4

6.4

15.0

18.2

32.8

29.8

3.8

1.1

8.3

17.3

7.3

0

Advances

1.7

0.9

3.2

16.1 1.6

Stressed advances

1.8

3.1

19.7

2.2

Source RBI, Financial Stability Report, June 2015

Within the three categories of banks if one looks at power generation, implications of its high leverage and financial fragility are showing up more for the public sector banks than for foreign-owned banks (see Table 10.1). On the other hand, for telecommunications, picture is the opposite. It is obvious that the contagion effects of higher leverage will affect the banking system only to the extent that their credit is exposed to these sectors. So, even with a perfectly normal macroeconomic picture of not so high leverage, there could be certain sectors with precarious financial conditions for which certain lending institutions have greater exposure. Despite the overall banking condition being normal and despite the macroeconomic condition being normal one could have a Minskyan instability building up underneath in certain sectors and through them to those banks which are exposed to these. This process can surely affect the macroeconomic conditions. Compare two situations. Situation 1 in which micro and macro conditions of leverage are the same. In such a situation, Minsky’s hypothesis is plain wrong. Situation 2 in which micro (obviously only in certain sectors) diverges from macro. Minsky is back with a vengeance. Concentration of bad debt both from the borrowers’ side and the lenders’ side makes the system susceptible to a financial crisis. Even though the overall banking system may not seem under threat, a few highly leveraged industries and a few large banks with high non-performing assets can create a general state of credit squeeze which can choke the system. I believe this is what the Indian economy is witnessing today.

10.3 Reinterpreting Minsky In light of the preceding discussion, one needs to reformulate the Minskyan story of financial fragility. A simple macroeconomic relationship can help show the fallacy in Minsky. For simplicity, we assume that all wages are consumed and all profits saved. Investment is financed partly through retained earnings of the firms and partly through debt. But the same act of investment also ipso facto generates aggregate demand, and hence, profits. This macroeconomic equilibrium tells us that higher

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debt taken to finance investment will necessarily generate profits pari passu so a divergence between the two is a macroeconomic impossibility. That is not to say that macroeconomic systems do not become financially fragile but that fragility cannot arise out of the specific route that Minsky had imagined. One should, however, not take this conclusion too far. What this macroeconomic relationship tells us is that since investment generates an equivalent amount of profits (under the simplifying assumptions we made), debt financing cannot be a problem for the corporate sector as a whole. But such a harmonious relationship between leverage and profits need not exist at the level of the industries. This relationship could break down at the industrial level if the investment of industry A, say predominantly driven by debt, generates more profits in industry B. This would increase the leverage in A with perhaps no countervailing decline in lever-age in B if this industry is primarily internally financed. From the lender’s side, if a subset of banks is exposed more to sector A, they will face serious financial conditions even though the banking sector as a whole may not be. Let me elaborate on this. Going back to Minsky’s famous scissor diagram, the shape of the demand price of capital schedule is drawn independent of the nature of competition in the industry whereas the latter should surely have an effect on the demand price. A horizontal demand price gives the impression as if the firms have an unlimited market and the only limiting factor to their investment is their access to capital. A horizontal demand price of capital may be true for industries, which have not yet matured into established oligopolies, i.e. industries in which large firms are still competing to establish their market shares? This would give us the usual Minskyan demand price schedule. The flat continuous portion of the MEI depicts the possibilities of expanding a firm’s share at the cost of its competitors in the same industry (see industry A in Fig. 10.5). Minsky’s QA QA curve has been drawn based on the retained earning of industry A in the previous year. If, however, an industry (Industry B in Fig. 10.5) is functioning strictly under conditions of established oligopolies, where it is near impossible to expand the market share of a firm through price cutting, the limit to investment of a firm is set by its expectations about the rate at which the industry itself expands (a proxy of which could be firm’s past capacity utilization). Under such conditions, the demand price of capital should be a vertical schedule at the level corresponding to expectations about demand (see Industry B in Fig. 10.5). Minsky’s QB QB curve has been drawn based on the retained earning of industry B in the previous year. As can be seen, for such industries, the rate of interest or the amount of credit available will have no influence on the investment level. Irrespective of where the Q-curve cuts the supply price curve, the level of investment is given by the vertical position of the MEI curve. Such industries are demand-constrained and not credit constrained. In the specific case drawn here, investment in industry B is financed entirely through retained earnings since the QB QB curve cuts the supply price PsB to the right of the vertical demand price curve Pd B . The scenario discussed above can be visualized through these two industries. As a result of booming conditions in the economy, firms in both industry A and B make

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Q

P

P

d

d

P’ PAs

P

s

Q’B Q

Q

IA

IB

Industry A: Credit Constrained Industry Industry B: Demand Constrained Industry Fig. 10.5 Minsky’s instability hypothesis at a disaggregated level

investments. To begin with investment, industry A is financed partly internally and part through debt whereas in B it’s financed entirely through retained earnings. This investment generates an equivalent amount of profit, which should shift the internal funds curve QQ outward. This would have happened in both the industries if the macro and micro conditions were the same. But we are interested in a scenario when they are not. Without loss of generality, let’s say that investment in plants in industry A accrue largely to B, which produces material used for A, which pushes the QB QB curve outward in the next period. Assuming profits in industry A remain the same as they were earlier QA QA curve stays put. It is not that difficult to imagine such a situation. Let’s say industry A is Power, which has a huge gestational lag because of which it can’t generate any profits within just yet. Such a situation could arise purely on account of miscalculation in industry A or perhaps even with collusion of the corporations and the lending agencies. All or any of this would lead to a fall in the demand price post facto. If the fall is to P'A d , which is lower than the interest commitments of this industry, this industry would have moved from a hedged position to speculative. It is here that the regulating authorities need to intervene but in conditions of macro buoyancy, such micro-level fragilities may go overlooked or, worse still, aggravated. How? Minsky’s endogenous credit boom could come into play, only this time at the industry level. Banks being confident about the macroeconomic condition in general and in their pursuit of profits may let their guards down by relaxing credit norms or even taking a price cut in the expectation of more than compensating the price loss in terms of gain in quantity of loans advanced. From the borrower’s side, this one time fall in profitability may not affect their long-term projection of the demand price and they may also become less prudent in terms of increasing their leverage by lowering borrower’s risk. Lowering of both the lender’s and borrower’s risk as a result of macroeconomic buoyancy can, however, create a micro-level financial fragility over the same period of time.

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This opening up of the scissor increases the leverage in industry A over time. But after all this investment is generating profits in industry B. Shouldn’t that just cancel out this rise in leverage in A? There is an asymmetry here. While the leverage of A rises, there is no (or a relatively smaller) counterpart in B because it was not (or only marginally) leveraged in the first place, as shown here. At the level of industry B, there’s a windfall since not only does it get its own profits, it also gets the profits arising out of the investment process in industry A, so its internal funds curve QB QB shifts outward. But such an outward shift has little or no effect on the leverage of this industry because it was not constrained by finance to begin with. At any given point in time, there will be mature industries, where demand (vertical MEI) sets the limit to invest with no role of finance, as well a nascent industries, where demand (by influencing the MEI) as well as finance constraint (through borrower’s and lender’s risk) together set the limit to investment that the firms would like to undertake. The reason why financial fragility of industry A is not getting canceled by the cushion provided by higher profits in industry B is because while A’s lack of profitability hampers its ability to honor its interest commitments to the lending institutions, the corresponding rise in profits of B doesn’t show up in the balance sheet of the lending institutions since B’s investment is not limited by finance and hence its relative independence from these institutions. This would not have been the case had both the industries been credit constrained in the same way. In such a situation even if the profitability in A was missing, the rise in leverage of A would have been equally compensating for by the fall in leverage of B and hence would not have threatened the financial viability of the lending institutions. Moreover, with the simultaneous existence of credit constrained as well as demand-constrained industries, if bad debt, instead of being spread across different lending institutions, is concentrated in just a few, financial fragility takes an altogether different dimension. If a large part of power generation NPAs is concentrated in two to three banks, it is obvious that not only does it create a precarious situation for these banks, it also creates conditions for credit squeeze for otherwise creditworthy investment projects. The scare forces these banks, and in wake of it to all the other banks as well, to be wary of lending. This chokes the credit-dependent industries, which in turn, through the multiplier, affects the other demand-constrained industries as well. So, this creates an endogenous cycle of financial instability. This distinction of industries in these two groups will help us also isolate the cases of exogenous financial fragility generated by sudden decline in profitability of enterprise as a result of demand or supply shocks, from those endogenously generated as a result of the functioning of the financial architecture. Since such shocks cannot be anticipated, taming the first kind of business cycle is a rather difficult task and regulating authorities can only play a limited role. To conclude, Minsky’s business cycle was of the endogenous variety but as shown above it suffers from a serious macroeconomic fallacy which makes his argument invalid. To put it rather strongly, stability cannot create instability at a macro level since stability creates more stability. But stability, under certain circumstances, can camouflage instability beneath. The role of the regulating authority is to keep a tab on

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the extent of instability building up underneath and intervene at appropriate moments to avoid knee-jerk reactions of credit squeeze, which would worsen the matters by adding an exogenous shock to an otherwise endogenously created downturn.

References Lavoie M, Seccareccia M (2001) Minsky’s financial fragility hypothesis: a missing macroeconomic link. In: Bellofiore R, Ferri P (eds) Financial fragility and investment in the capitalist economy: the economic legacy of Hyman Minsky, 2, pp 76–96 Minsky HP (1975) John Maynard Keynes. Columbia University Press, New York Minsky HP (1981) Financial markets and economic instability, 1965–1980. Neb J Econ Bus 20(4):5– 16 Minsky HP (1983) Stabilizing an unstable economy. McGraw-Hill Education Minsky HP (2016) Can“it”happen again?: Essays on instability and finance. Routledge. 2016 Edition